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savjeecoin-frontend | p align center a href rel noopener img width 450px height 200px src https savjee github io savjeecoin frontend assets img github project logo png alt project logo a p h3 align center savjeecoin frontend h3 div align center build status https travis ci org savjee savjeecoin frontend svg branch master https travis ci org savjee savjeecoin frontend github issues https img shields io github issues savjee savjeecoin frontend svg https github com savjee bearclaw issues github pull requests https img shields io github issues pr savjee savjeecoin frontend svg https github com savjee bearclaw pulls license https img shields io badge license mit blue svg license div angular application that allows you to interact with a blockchain you can see the blocks on chain see transaction within them and even create new transactions and mine blocks built on top of savjeecoin https github com savjee savjeecoin simply blockchain implementation in javascript live demo check it out here https savjee github io savjeecoin frontend you can create transactions mine blocks and explore your own blockchain getting started a name getting started a get a copy of the savjeecoin front end running on your local machine for playing around testing or development git clone https github com savjee savjeecoin frontend git install the dependencies cd savjeecoin frontend npm install run the application npm start at this point the application should be running on your machine on http localhost 4200 http localhost 4200 screenshots home page seeing blocks on the chain exploring transactions in each block https savjee github io savjeecoin frontend assets screenshots blockchain overview png creating new transactions you can create new transactions to any wallet for any amount no validation new transactions will be added to the pending transactions ready to be included in the next block https savjee github io savjeecoin frontend assets screenshots create new transactions png pending transactinos list of all pending transactions these will be included in the next block when the mining process starts https savjee github io savjeecoin frontend assets screenshots pending transactions png wallet details you can click on any wallet address and see an overview of that wallet its current balance and all transaction to from that wallet https savjee github io savjeecoin frontend assets screenshots wallet details png this is for educational purposes only this is by no means a complete blockchain implementation nor does it aim to be one use it to learn how blockchains operate | blockchain js proof-of-concept angular front-end | blockchain |
femaleit | femaleit github io | server |
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ICT | ict information central technology | server |
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Android | mobilne informacione tehnologije github strana sa materijalima za kurs mobilne informacione tehnologije u okviru ovog repo a nalaze se primeri android aplikacija koji bi sluzili kao domonstracija osnovnih mogucnosti takodje nalaze se primeri razvoja android aplikacija koje koriste mbaas i cloud podrsku za svoje klijente u wiki https github com mit vezbe android wiki sekciji mozete naci detaljniji opis i spisak svih aplikacija i dodatnih materijala koje ce vam pomoci u upoznavanju sa razvojem android mobilnih aplikacija prezentacije https github com mit vezbe android tree master presentations sa vezbi ce vam pomoci za bolje razumevanje mogucnosti koje android platforma pruza za razvoj mobilnih aplikacija u oviru sekcije za projekte https github com mit vezbe android tree master projects podizacete vase implementacije u hierarhiji foldera koji su vec predodredjeni u oviru sekcije za pokazne primere https github com mit vezbe android tree master basicsamples mozete naci osnovne primere za upotrebu glavnih funkcionalnosti android api a | server |
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Smart-Home-Project-AVR-ATmega32- | smart home project avr atmega32 overview this is an embedded systems project in which a smart home is designed using atmega32 on proteus simulation and can be installed on hardware it is a common project topic however i found it is crucial to conduct this project that uses several hardware drivers and requires good logic this smart home can be controlled by two types of users an admin who controls the system remotely through a device that uses bluetooth as a phone represented here using hc 06 bluetooth module and users who control the smart home directly through the hardware components connected to the microcontroller you can control 6 rooms lights with one room having dimmer light door movement open close air conditioner on off parameters and drivers used clock frequency 1mhz br mcal dio i2c gie timer0 timer1 and uart baud rate 2400 br hal lcd keypad eeprom start the system starts by showing a message to start press 0 on both admin s and users screens this is done to ensure serializability of smart home access between the admin remotely and users either the admin or any user whoever presses 0 first a session starts to this same person and the other has to wait until this session ends admin s actions change password control 5 rooms lights on off and one room as dimmer set percentage open or close door turn on or off the ac add or remove users users actions control 5 rooms lights on off and one room as dimmer set percentage turn on or off the ac add or remove users system checks automatically that new user s name is not registered simulation start p align center img src https user images githubusercontent com 104737465 217668822 d9d5e2f2 3659 4f61 afd1 fc2d5751b984 png width 700 height 400 title hover text p flowchart flowchart pdf https github com seifbassiounyy smart home project avr atmega32 files 10670031 flowchart pdf | os |
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SmartTV | smarttv fun and useful data about smarttv web based development lg and samsung platform specs platform specs md nettv useragent strings for different vendors nettv user agents md samsung models demistified samsung models md lg models demistified lg models md keycodes of key events keycodes md | front_end |
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DevOpsInfo | devopsinfo important information for devops amp platform engineering in the microsoft cloud space | cloud |
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iotagent-node-lib | fiware iot agent node js library fiware iot agents https nexus lab fiware org static badges chapters iot agents svg https www fiware org developers catalogue license apgl https img shields io github license telefonicaid iotagent node lib svg https opensource org licenses agpl 3 0 support badge https img shields io badge tag fiware iot orange svg logo stackoverflow https stackoverflow com questions tagged fiware iot br documentation badge https img shields io readthedocs iotagent node lib svg http iotagent node lib readthedocs org en latest badge latest ci https github com telefonicaid iotagent node lib workflows ci badge svg https github com telefonicaid iotagent node lib actions query workflow 3aci coverage status https coveralls io repos github telefonicaid iotagent node lib badge svg branch master https coveralls io github telefonicaid iotagent node lib branch master status https nexus lab fiware org static badges statuses iot node lib svg cii best practices https bestpractices coreinfrastructure org projects 4671 badge https bestpractices coreinfrastructure org projects 4671 this project aims to provide a node js module to enable iot agent developers to build custom agents for their devices that can easily connect to ngsi context brokers such as orion https github com telefonicaid fiware orion an iot agent is a component that lets groups of devices send their data to and be managed from a fiware ngsi context broker using their own native protocols iot agents should also be able to deal with security aspects of the fiware platform authentication and authorization of the channel and provide other common services to the device programmer this project is part of fiware https www fiware org for more information check the fiware catalogue entry for the iot agents https github com fiware catalogue tree master iot agents books documentation https iotagent node lib rtfd io mortar board academy https fiware academy readthedocs io en latest iot agents idas dart roadmap https github com telefonicaid iotagent node lib blob master doc roadmap md index background background install install api api usage usage testing testing agent console agent console agent tester agent tester licence licence background the main concept of the iot agent node library is to provide a common framework for provisioning iot devices allowing each individual iot agent to access standardized mapping data for devices and to offer a series common utility functions for southbound communications the library listens to changes in context entities and raises callbacks for the iot agent to process for northbound communications the library offers an interface which accepts structured input data so that all ngsi communications are left to the library standardized oauth2 based security is available to enable each iot agent to connect to several common identity managers e g keystone and keyrock so that communications can be restricted to trusted components each individual iot agent offers is driven by a config js configuration file contains explicit custom settings based on the protocol and payload the iot agent is translating it will also contain some common flags for common functionality provided by the iot agent node lin e g for contecting to a conext broker or for authentication the iot agent node library offers a standard api for provisioning devices and ensures that each iot agent can configure its device communications using a common vocabulary regardless of the payload syntax or transport protocol used by the device itself install the iot agent node library is not a standalone product and should be added as a dependency to package json of the iot agent json dependencies iotagent node lib in order to use the library within your own iot agent you must first you require it before use javascript const iotagentlib require iotagent node lib information about how to configure the library can be found at the corresponding section of the installation administration guide doc admin md usage this library has no packaging or build processes the getting started doc getting started md is a good place to start you can also review the api documentation doc api md for a full list of the available functions if you plan to use the library in your own iot agent you should read the developer guide doc devel development md you can also review the architecture doc devel architecture md documentation and northbound api doc devel northbound api md the following features are listed as deprecated doc deprecated md api the iot agent node library offers a simple rest api which provides common functionality to access provision and decommission devices api doc api md testing contributions to development can be found here doc devel development md additional contributions are welcome agent console a command line client to experiment with the library is packed with it the command line client can be started using the following command console bin agentconsole js the client offers an api similar to the one offered by the library it can start and stop an iot agent register and unregister devices send measures mimicking the device and receive updates of the device data take into account that by default the console uses the same config js file than the iot agent the command line client creates a console that offers the following options text stressinit start recording a stress batch stresscommit delay times threads inittime executes the recorded batch as many times as requested with delay ms between commands the threads parameter indicates how many agents will repeat that same sequence the inittime ms parameter indicates the mean of the random initial waiting times for each agent exit exit from the command line start start the iot agent stop stop the iot agent register id type register a new device in the iot agent the attributes to register will be extracted from the type configuration unregister id type unregister the selected device showconfig show the current configuration file config newconfig change the configuration file to a new one updatevalue deviceid devicetype attributes update a device value in the context broker the attributes should be triads with the following format name type value sepparated by commas listdevices list all the devices that have been registered in this iot agent session agent tester command line testing the library also offers a context broker and iot agent client that can be used to simulate operations to the context broker used by the iot agent triggering context provider forwardings for lazy attributes and checking the appropriate values for active ones simulate operations to the device provisioning api and configuration api of the iot agent the tester can be started with the following command from the root folder of the project console bin iotagenttester js from the command line the help command can be used to show a description of the currently supported features these are the following text stressinit start recording a stress batch stresscommit delay times threads inittime executes the recorded batch as many times as requested with delay ms between commands the threads parameter indicates how many agents will repeat that same sequence the inittime ms parameter indicates the mean of the random initial waiting times for each agent exit exit from the command line update entity type attributes update the values of the defined set of attributes using the following format name type value name type value append entity type attributes append a new entity with the defined set of attributes using the following format name type value name type value query entity type get all the information on the selected object queryattr entity type attributes get information on the selected object for the selected attributes discover entity type get all the context providers for a entity and type configcb host port service subservice config a new host and port for the remote context broker showconfigcb show the current configuration of the client for the context broker configiot host port service subservice config a new host and port for the remote iot agent showconfigiot show the current configuration of the client for the iot agent provision filename provision a new device using the device provisioning api the device configuration is read from the file specified in the filename parameter provisiongroup template data type provision a group of devices with the selected template taking the information needed to fill the template from a csv with two columns device id and device name the third parameter type will be used to replace the device type field in the template all the devices will be provisioned to the same iot agent once the templates have been fulfilled listprovisioned list all the provisioned devices in an iot agent removeprovisioned deviceid remove the selected provisioned device from the iot agent specified by its device id addgroup filename add a new device group to the specified iot agent through the configuration api the body is taken from the file specified in the filename parameter listgroups list all the device groups created in the selected iot agent for the configured service removegroup apikey resource remove the device group corresponding to the current configured subservice authenticate host port user password service authenticates to the given authentication server and use the token in subsequent requests setprotocol protocol sets the protocol to use in the requests http or https defaults to http configmigration host port origindb sets the configuration for a migration between a c iota and a node js one showconfigmigration shows the current migration configuration addprotocols protocols add a protocol translation table in the following format protocolorigin1 protocoltarget1 protocolorigin2 protocoltarget2 migrate targetdb service subservice migrate all the devices and services for the selected service and subservice into the specified mongo database to perform the migration for all the services or all the subservices use the value the agent session stores transient configuration data about the target context broker and the target iot agent this configuration is independent and can be checked with the showconfigcb and showconfigiot commands respectively their values can be changed with the configcb and configiot commands respectively the new configurations will be deleted upon startup licence the iot agent node library is licensed under affero general public license gpl version 3 license 2022 telefonica investigaci n y desarrollo s a u are there any legal issues with agpl 3 0 is it safe for me to use there is absolutely no problem in using a product licensed under agpl 3 0 issues with gpl or agpl licenses are mostly related with the fact that different people assign different interpretations on the meaning of the term derivate work used in these licenses due to this some people believe that there is a risk in just using software under gpl or agpl licenses even without modifying it for the avoidance of doubt the owners of this software licensed under an agpl 3 0 license wish to make a clarifying public statement as follows please note that software derived as a result of modifying the source code of this software in order to fix a bug or incorporate enhancements is considered a derivative work of the product software that merely uses or aggregates i e links to an otherwise unmodified version of existing software is not considered a derivative work and therefore it does not need to be released as under the same license or even released as open source | fiware iot iot-agent | server |
moko-permissions | moko permissions img logo png github license https img shields io badge license apache 20license 202 0 blue svg style flat http www apache org licenses license 2 0 download https img shields io maven central v dev icerock moko permissions https repo1 maven org maven2 dev icerock moko permissions kotlin version https kotlin version aws icerock dev kotlin version group dev icerock moko name permissions mobile kotlin runtime permissions multiplatform controller moko permissions kotlin multiplatform library for providing runtime permissions on ios android table of contents features features requirements requirements installation installation list of supported permissions list of supported permissions usage usage samples samples set up locally set up locally contributing contributing license license features permission enumeration with primary types of device permissions permissionscontroller handler for runtime permission requests can be used in the common code with lifecycle safety for android deniedexception and deniedalwaysexception exceptions to handle user denial of permissions compose multiplatform support requirements gradle version 6 8 android api 16 ios version 11 0 installation root build gradle groovy allprojects repositories mavencentral project build gradle groovy dependencies commonmainapi dev icerock moko permissions 0 16 0 compose multiplatform commonmainapi dev icerock moko permissions compose 0 16 0 permissions api compose extensions commontestimplementation dev icerock moko permissions test 0 16 0 list of supported permissions the full list can be found in dev icerock moko permissions permission enum camera permission camera gallery permission gallery storage read permission storage storage write permission write storage fine location permission location coarse location permission coarse location remote notifications permission remote notification audio recording permission record audio bluetooth le permission bluetooth le bluetooth scan permission bluetooth scan bluetooth connect permission bluetooth connect bluetooth advertise permission bluetooth advertise usage common code kotlin class viewmodel val permissionscontroller permissionscontroller viewmodel fun onphotopressed viewmodelscope launch try permissionscontroller providepermission permission gallery permission has been granted successfully catch deniedalways deniedalwaysexception permission is always denied catch denied deniedexception permission was denied android kotlin override fun oncreate savedinstancestate bundle super oncreate savedinstancestate val viewmodel getviewmodel pass the platform implementation of the permission controller to a common code viewmodel permissionscontroller binds the permissions controller to the activity lifecycle viewmodel permissionscontroller bind lifecycle supportfragmentmanager compose kotlin composable fun testscreen val viewmodel getviewmodel pass the platform implementation of the permission controller to a common code viewmodel permissionscontroller binds the permissions controller to the locallifecycleowner lifecycle bindeffect viewmodel permissionscontroller ios swift just pass the platform implementation of the permission controller to a common code let viewmodel viewmodel permissionscontroller permissionscontroller compose multiplatform kotlin composable fun sample val factory permissionscontrollerfactory rememberpermissionscontrollerfactory val controller permissionscontroller remember factory factory createpermissionscontroller val coroutinescope coroutinescope remembercoroutinescope button onclick coroutinescope launch controller providepermission permission remote notification text text give permissions or with moko mvvm with correct configuration change handle on android kotlin composable fun sample val factory permissionscontrollerfactory rememberpermissionscontrollerfactory val viewmodel permissionsviewmodel getviewmodel key permissions screen factory viewmodelfactory permissionsviewmodel factory createpermissionscontroller bindeffect viewmodel permissionscontroller button onclick viewmodel onbuttonclick text text give permissions class permissionsviewmodel val permissionscontroller permissionscontroller viewmodel fun onbuttonclick viewmodelscope launch permissionscontroller providepermission permission remote notification samples more examples can be found in the sample directory sample set up locally in permissions directory permissions contains permissions library in sample directory sample contains samples on android ios mpp library connected to apps contributing all development both new features and bug fixes is performed in develop branch this way master sources always contain sources of the most recently released version please send prs with bug fixes to develop branch fixes to documentation in markdown files are an exception to this rule they are updated directly in master the develop branch is pushed to master during release more detailed guide for contributers see in contributing guide contributing md license copyright 2019 icerock mag inc licensed under the apache license version 2 0 the license you may not use this file except in compliance with the license you may obtain a copy of the license at http www apache org licenses license 2 0 unless required by applicable law or agreed to in writing software distributed under the license is distributed on an as is basis without warranties or conditions of any kind either express or implied see the license for the specific language governing permissions and limitations under the license | android ios kotlin-native kotlin-multiplatform moko coroutines kotlin-multiplatform-mobile | front_end |
Udacity-Data-Engineering-Projects | udacity data engineering projects https github com saurabhsoni5893 udacity data engineering projects blob master dataengineering jpg project 1 data modeling with postgres a startup called sparkify want to analyze the data they have been collecting on songs and user activity on their new music streaming app the analytics team is particularly interested in understanding what songs users are listening to the aim is to create a postgres database schema and etl pipeline to optimize queries for song play analysis link data modeling with postgres https github com saurabhsoni5893 udacity data engineering projects tree master data modeling with postgres project 2 data modeling with apache cassandra in this project i would be applying data modeling with apache cassandra and complete an etl pipeline using python i will build a data model around my queries that i want to get answers for for my use case i want below answers get details of a song that was herad on the music app history during a particular session get songs played by a user during particular session on music app get all users from the music app history who listened to a particular song link data modeling with apache cassandra https github com saurabhsoni5893 udacity data engineering projects tree master data modeling with apache cassandra project 3 data warehouse with aws project is related to application of data warehouse and aws to build an etl pipeline for a database hosted on redshift i will need to load data from s3 to staging tables on redshift and execute sql statements that create fact and dimension tables from these staging tables to create analytics use redshift iac script redshift iac readme https github com saurabhsoni5893 udacity data engineering projects blob master redshift iac readme md link data warehouse with aws https github com saurabhsoni5893 udacity data engineering projects tree master data warehouse with aws project 4 data lake with apache spark in this project i will build a data lake on aws cloud using spark and aws emr cluster the data lake will serve as a single source of truth for the analytics platform i will write spark jobs to perform elt operations that picks data from landing zone on s3 and transform and stores data on the s3 processed zone link data lake with spark https github com saurabhsoni5893 udacity data engineering projects tree master data lakes with spark project 5 data pipelines with airflow in this project i will orchestrate the data pipeline workflow using an open source apache project called apache airflow i will schedule our etl jobs in airflow create project related custom plugins and operators and automate the pipeline execution link data pipelines with airflow https github com saurabhsoni5893 udacity data engineering projects tree master data pipelines with airflow | data data-engineering data-engineer-nanodegree data-engineering-nanodegree postgresql-database cassandra-database data-modeling data-warehouse data-lake aws aws-ec2 aws-s3 emr-cluster airflow data-pipeline | cloud |
sql-data-engineering | this research project involves creating a database of people whom pewlett hackard employed during the 1980s and 1990s all that remains of the employee database from that period are six csv files for this project i designed the tables to hold the data from the csv files imported the csv files into a sql database and then answered questions about the data this project was completed according to the following workflow data modeling inspect the csv files and then sketch an erd of the tables data engineering use the provided information to create a table schema for each of the six csv files be sure to do the following remember to specify the data types primary keys foreign keys and other constraints for the primary keys verify that the column is unique otherwise create a composite keylinks to an external site which takes two primary keys to uniquely identify a row be sure to create the tables in the correct order to handle the foreign keys import each csv file into its corresponding sql table data analysis list the employee number last name first name sex and salary of each employee list the first name last name and hire date for the employees who were hired in 1986 list the manager of each department along with their department number department name employee number last name and first name list the department number for each employee along with that employee s employee number last name first name and department name list first name last name and sex of each employee whose first name is hercules and whose last name begins with the letter b list each employee in the sales department including their employee number last name and first name list each employee in the sales and development departments including their employee number last name first name and department name list the frequency counts in descending order of all the employee last names that is how many employees share each last name use the following code to begin from sqlalchemy import create engine engine create engine postgresql localhost 5432 your db name connection engine connect create a histogram to visualize the employee salary ranges that were the most common create a bar chart of average salary by title create an image file of your erd create a sql file of your table schemata create a sql file of your queries methods used sql jupyter notebooks erd primary keys | data-modeling database erd sql | server |
oaq-esp-open-rtos | our air quality logger for the esp8266 running the esp open rtos https github com superhouse esp open rtos a community developed open source air quality data logger currently supporting the plantower http plantower com pms1003 pms3003 pms5003 and pms7003 particle counters supports a few temperature relative humidity and pressure sensors on the same i2c these are auto detected and used if available this data might be important for qualifying if the air conditions support reliable pm measurement bme280 temperature relative humidity and air pressure sensor sht2x temperature and relative humidity sensors bmp180 temperature and air pressure sensor the ds3231 real time clock is also supported on the i2c bus and used if available the time is logged periodically and synchronsized to the time that the http server sends in its responses this can be very helpful when logging data away from wifi and internet access so that measurments are correctly time stamped building follow the build instructions for esp open rtos and when the examples are running copy this code into examples oaq this code supports a 4mib spi flash so the esp12 and the nodemcu and witty boards have been tested for this flash it was necessary to edit parameters mk to change flash size 32 and flash mode dio the following will build the code and flash a device on linux make flash j4 c examples oaq espport dev ttyusb0 features logs the data to a memory buffer and then to the spi flash storage using 3mib of the 4mib for data storage this allows the data logger to be used out of reach of wifi and the internet for a period all the data from the plantower sensor is logged each sample at 0 8 second intervals and all the data in the samples which includes the pm1 0 pm2 5 and pm10 values plus the particle counts and even the checksum for each sample this might be useful for local sources of pollution that can cause quick changes in air quality and might be useful for post analysis such as noise reduction the data is compressed to fit more data into the flash and this also reduces wear on the flash and perhaps power usage the particle count distributions are converted to differential values reducing their magnitude and after delta encoding they are encoding using a custom variable bit length code there are special events for the case of no change in the values in which case only a time delta is encoded this typically compresses the data to 33 to 15 of the original size the compressed data is stored in flash sectors and each sector stands on its own and can be uncompressed on its own an attempt is made to handle bad sectors in which case the data is written to the next good sector each valid sector is assigned a monotonically increasing 32 bit index the sectors are organized as a ring buffer so when full the oldest is overwritten the sectors are buffered in memory before writing to reduce the number of writes and the current data is periodically flushed to the flash storage to avoid too much data loss if power is lost esp flash tools can read these sectors for downloading the data without wifi the compressed sectors are http posted to a server the current head sector is periodically posted to the server too to keep it updated and only the new data is posted the server response can request re sending of sectors still stored on the device to handle data loss at the server the server can not affected the data stored on the device or the logging of the data to flash as a safety measure the esp8266 real time clock rtc counter is logged with every event the server response includes the real time and response events are logged allowing estimation of the real time of events in post analysis this can be be supported by the optional ds3231 real time clock support for logging a button press will be added to allow people to synchronize logging and events times manually the data posted to the server is signed using the mac sha3 algorithm ensuring integrity of the data and preventing forgery of data posted to the server connection two esp8266 boards have been tested nodemcu uart pins for the pmsx003 pcb name function cable color vin 5v purple gnd 0v orange d7 rx green d8 tx blue note the lolin v3 nodemcu board vin pin is not usable as a 5v output but it has 5v output on it s vu pin which is a reserved pin on other nodemcu boards note the tx line is to be not connect at present as the device sends verbose debug output on the serial line that might affect the sensor i2c pins pcb name function d1 scl d2 sda 3v3 v g ground witty uart pins for the pmsx003 pcb name function cable color vin 5v purple gnd 0v orange rx rx green tx tx blue i2c pins pcb name function gpio5 scl gpio4 sda vcc v g ground configuration the configuration is stored in the esp free rtos sysparam database see the esp free rtos sysparam example for an editor which can be used to set these for now the database uses four more sectors at the end of the flash board single binary byte that can be 0 for nodemcu and 1 for witty it is only used to blink some leds at present pms uart single binary byte that gives the pms 003 serial port 0 none disabled default 1 uart0 on gpio3 aka rx nodemcu pin d9 2 uart0 swapped pins mode gpio13 nodemcu pin d7 3 todo flipping between the above for two sensors i2c scl i2c sda single binary bytes giving the i2c bus pin definitions gpio numbers scl defaults to gpio 0 nodemcu pin d3 and sda to gpio 2 nodemcu pin d4 if not supplied the follow are network parameters if not sufficiently initialized to communicate with a server then wifi is disabled and the post data task is not created but the data will still be logged to the internal flash storage and can be downloaded to a pc web server a string e g ourairquality org 192 168 1 1 web port a string e g 80 web path a string e g cgi bin recv sensor id a binary 32 bit number key size a binary 32 bit number sha3 key a binary blob with key size bytes wifi ssid a string the wifi station id wifi pass a string the respective wifi password todo this is at the proof of concept stage the url to upload the data to and the key is hard coded see post c and this needs to be configurable todo a web client app to create the sysparam sectors the server side code for logging the data to files has been prototyped and is cgi code written in a few pages of c code and tested on apache and expected to work on economical cpanel shared hosting the client front end is stil todo and is just some hack scripts for now | os |
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TipHero | project 1 tiphero tiphero is a tip calculator application for ios submitted by sarah gu time spent 6 hours spent in total user stories the following required functionality is complete x user can enter a bill amount choose a tip percentage and see the tip and total values the following optional features are implemented settings page to change the default tip percentage x ui animations remembering the bill amount across app restarts if 10mins using locale specific currency and currency thousands separators x making sure the keyboard is always visible and the bill amount is always the first responder this way the user doesn t have to tap anywhere to use this app just launch the app and start typing the following additional features are implemented x added calculation for the amount of money per person x changed background color for ease of readibility video walkthrough here s a walkthrough of implemented user stories video walkthrough https github com sarah gu tiphero blob main tipherodemo gif notes it was difficult to add in the functionality of calculating tip divided amongst people because i had to figure out how to integrate the tools without the guidance of a tutorial another challenge i faced was in animating the movement of the bill field and trying to get the other fields to hide without impacting the former credits tutorial given by codepath license copyright 2021 sarah gu licensed under the apache license version 2 0 the license you may not use this file except in compliance with the license you may obtain a copy of the license at http www apache org licenses license 2 0 unless required by applicable law or agreed to in writing software distributed under the license is distributed on an as is basis without warranties or conditions of any kind either express or implied see the license for the specific language governing permissions and limitations under the license | os |
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bitshares-ui | bitshares ui readme zh md this is the reference wallet of bitshares blockchain which connects to bitshares blockchain nodes bitshares core this reference wallet is a browser based wallet which means your keys are stored locally in your browser and never leaves it while using the wallet you should never expose your keys to anyone as transactions are signed locally before transmitting them to a node getting started building bitshares ui browser based reference wallet depends on node version 16 using a non root user on ubuntu or macos the easiest way to install node is to use node version manager https github com creationix nvm install nvm according to your platforms recommendation and set the version nvm install v16 nvm use v16 once you have node installed clone the repository using the following commands git clone https github com bitshares bitshares ui git cd bitshares ui before launching the ui you will need to install the packages using yarn on a non root user yarn install running the dev server once all the packages have been installed you can start the development server by running yarn start once the compilation is done the ui will be available in your browser at localhost 8080 or 127 0 0 1 8080 hot reloading is enabled so the browser will live update as you edit the source files testnet by default bitshares ui connects to the bitshares mainnet but it s very easy to switch it to the testnet to do so open the ui in a browser go to settings then under nodes select the testnet in the dropdown menu the ui will reload and connect to the testnet there is also a ready made deployment directly connected to testnet including account creation available here https test xbts io image https user images githubusercontent com 33128181 175760811 736c9b21 9122 4160 bd30 465bb755a3a3 png production if you d like to host your own ui somewhere you should create a production build and host it using nginx or apache in order to create a prod bundle simply run the following command yarn run build this will create a bundle in the build dist folder that can be hosted with the web server of your choice installable local wallet we use electron to provide installable wallets available for windows macos and linux debian platforms such as ubuntu there is a github action available https github com bitshares bitshares ui blob master github workflows build release binaries yml l18 that shows all the steps necessary for this build this will compile the ui with some special modifications for use with electron generate installable binaries with electron and copy the result to the root build binaries folder docker clone this repository run docker compose up and visit localhost 8080 contributing coding style guideline see contributing md contributing md code of conduct this repository has a code of conduct that should be followed by everyone please read code of conduct md code of conduct md please keep comments constructive and clean browserstack the bitshares ui is integrated with browserstack https www browserstack com to allow manual compatibility testing across devices and browser versions in the future we will switch to a automated selenium testing framework image https user images githubusercontent com 33128181 48697885 05f8d880 ebe6 11e8 95a2 d87516cbb3d9 png release branches there are three branches that forms the current release process develop all prs should be pushed to the develop branch new commits are automatically deployed to this branch and published for review available for browsing on https develop bitshares org staging current release candidate at the end of each milestone develop branch is pushed to staging and forms the release candidate the date of the rc forms the name ie 5 0 220214 rc1 application breaking issues and bugs should be submitted to the issue tracker and prs should be pushed to staging available for browsing on https staging bitshares org master stable when all major issues to the current rc are fixed staging branch is released to the stable master branch available for browsing on https wallet bitshares org which is the official reference wallet for bitshares | bitshares cryptocurrency blockchain-wallet bitshares-ui wallet blockchain web-app javascript reactjs | blockchain |
lecture_code | python python binder https mybinder org badge logo svg https mybinder org v2 gh tttamaki lecture code git main machinelearningmath machinelearningmath python https www udemy com course cvmathbasic open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath check mat vec mul ipynb check mat vec mul ipynb machinelearningmath check mat vec mul ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath face reconstruction ipynb face reconstruction ipynb machinelearningmath face reconstruction ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath numpy neural net ipynb numpy neural net ipynb machinelearningmath numpy neural net ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath differentiation scipy ipynb differentiation scipy ipynb machinelearningmath differentiation scipy ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath differentiation sympy ipynb differentiation sympy ipynb machinelearningmath differentiation sympy ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath differentiation autograd ipynb differentiation autograd ipynb machinelearningmath differentiation autograd ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath optimization ipynb optimization ipynb machinelearningmath optimization ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath face reconstruction via optimization ipynb face reconstruction via optimization ipynb machinelearningmath face reconstruction via optimization ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath face reconstruction via sparse regression ipynb face reconstruction via sparse regression ipynb machinelearningmath face reconstruction via sparse regression ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath face inpainting via regression ipynb face inpainting via regression ipynb machinelearningmath face inpainting via regression ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath face reconstruction low dimension ipynb face reconstruction low dimension ipynb machinelearningmath face reconstruction low dimension ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath face reconstruction via ista fista ipynb face reconstruction via ista fista ipynb machinelearningmath face reconstruction via ista fista ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath face reconstruction via admm ipynb face reconstruction via admm ipynb machinelearningmath face reconstruction via admm ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath classification perceptron logistic ipynb classification perceptron logistic ipynb machinelearningmath classification perceptron logistic ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath classification neural net ipynb classification neural net ipynb machinelearningmath classification neural net ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath classification neural net multiclass ipynb classification neural net multiclass ipynb machinelearningmath classification neural net multiclass ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main machinelearningmath classification logistic reg multiclass ipynb classification logistic reg multiclass ipynb machinelearningmath classification logistic reg multiclass ipynb imageprocessing imageprocessing scikit image opencv pil scipy python https www udemy com course image processing python open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main imageprocessing 1 image pixel binary ipynb 1 image pixel binary ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main imageprocessing 2 movie transform ipynb 2 movie transform ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main imageprocessing 3 filtering spectrum ipynb 3 filtering spectrum ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main imageprocessing 4 restoration segmentation pattern ipynb 4 restoration segmentation pattern ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main imageprocessing 5 clustering ipynb 5 clustering ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main imageprocessing 5 face classification ipynb 5 face classification ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main imageprocessing 5 pattern recognition deep ipynb 5 pattern recognition deep ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main imageprocessing 5 deep learning classification dog cat ipynb 5 deep learning classification dog cat ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main imageprocessing 6 imaging process ipynb 6 imaging process ipynb open in collab https colab research google com assets colab badge svg https colab research google com github tttamaki lecture code blob main imageprocessing 7 3d reconst color ipynb 7 3d reconst color ipynb colab skimage pillow pip install u scikit image pillow | ai |
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nlparse | zensols natural language parsing pypi pypi badge pypi link python 3 9 python39 badge python39 link python 3 10 python310 badge python310 link build status build badge build link this framework wraps the spacy framework and creates light weight features in a class hierarchy that reflects the structure of natural language the motivation is to generate features from the parsed text in an object oriented fashion that is fast and easy to pickle see the full documentation paper on arxiv http arxiv org abs 2109 03383 other features include parse and normalize a stream of tokens as stop words punctuation filters up down casing porter stemming and others detached features that are safe and easy to pickle to disk configuration drive parsing and token normalization using configuration factories pretty print functionality for easy natural language feature selection a comprehensive scoring module including following scoring methods rouge bleu semeval 2013 task 9 1 levenshtein distance exact match documentation framework documentation natural language parsing list token normalizers and mappers obtaining installing the easiest way to install the command line program is via the pip installer since the package needs at least one spacy module the second command downloads the smallest model bash pip3 install use deprecated legacy resolver zensols nlp python m spacy download en core web sm binaries are also available on pypi usage a parser using the default configuration can be obtained by python from zensols nlp import featuredocumentparser parser featuredocumentparser featuredocumentparser default instance doc parser obama was the 44th president of the united states for tok in doc tokens print tok norm tok pos tok tag print doc entities obama propn nnp was aux vbd the det dt 45th adj jj president noun nn of adp in the united states det dt punct obama 45th the united states however minimal effort is needed to configure the parser using a resource library python from io import stringio from zensols config import importiniconfig importconfigfactory from zensols nlp import featuredocument featuredocumentparser config import the zensols nlp library import config file resource zensols nlp resources obj conf override the parse to keep only the norm ent doc parser token feature ids set ent tag if name main fac importconfigfactory importiniconfig stringio config doc parser featuredocumentparser fac doc parser sent he was george washington and first president of the united states doc featuredocument doc parser sent for tok in doc tokens tok write this uses a resource library to source in the configuration from this package so minimal configuration is necessary more advanced configuration examples are also available see the feature documents for more information attribution this project or example code uses spacy for natural language parsing msgpack and smart open for python disk serialization nltk for the porter stemmer functionality citation if you use this project in your research please use the following bibtex entry bibtex article landes dieugenio caragea 2021 title deepzensols deep natural language processing framework url http arxiv org abs 2109 03383 note arxiv 2109 03383 journal arxiv 2109 03383 cs author landes paul and di eugenio barbara and caragea cornelia year 2021 month sep changelog an extensive changelog is available here changelog md license mit license license md copyright c 2020 2021 paul landes links pypi https pypi org project zensols nlp pypi link https pypi python org pypi zensols nlp pypi badge https img shields io pypi v zensols nlp svg python39 badge https img shields io badge python 3 9 blue svg python39 link https www python org downloads release python 390 python310 badge https img shields io badge python 3 10 blue svg python310 link https www python org downloads release python 310 build badge https github com plandes nlparse workflows ci badge svg build link https github com plandes nlparse actions examples https github com plandes nlparse tree master example config hierarchy https plandes github io nlparse api zensols nlp html zensols nlp container featuredocument parse and normalize https plandes github io nlparse doc parse html others https plandes github io nlparse doc normalizers html detached features https plandes github io nlparse doc parse html detached features full documentation https plandes github io nlparse framework documentation https plandes github io nlparse natural language parsing https plandes github io nlparse doc parse html list token normalizers and mappers https plandes github io nlparse doc normalizers html resource library https plandes github io util doc config html resource libraries spacy https spacy io nltk https www nltk org smart open https pypi org project smart open msgpack https msgpack org porter stemmer https tartarus org martin porterstemmer configuration factories https plandes github io util doc config html configuration factory feature documents https plandes github io nlparse doc feature doc html scoring module https plandes github io nlparse api zensols nlp html zensols nlp score rouge https aclanthology org w04 1013 bleu https aclanthology org p02 1040 semeval 2013 task 9 1 https web archive org web 20150131105418 https www cs york ac uk semeval 2013 task9 data uploads semeval 2013 task 9 1 evaluation metrics pdf levenshtein distance https en wikipedia org wiki levenshtein distance | spacy spacy-nlp nlp-machine-learning natural-language-processing pypi-link pypi-badge | ai |
Online-Movie-Ticket-Reservation-System | online movie ticket reservation system this is our database mini project we had done during the 5th semester of engineering as part of the curriculum | server |
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Automatic-Text-Summarizer | automatic text summarizer automatic document summarizer using bipartite hits natural language processing nlp | ai |
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spellbook-of-modern-webdev | h1 align center spellbook of modern web dev h1 div align center em a big picture thesaurus and taxonomy of modern javascript web development em div br br br br div align center img src assets cover png alt spellbook of modern web dev width 256 div br br br br this document originated from a bunch of most commonly used links and learning resources i sent to every new web developer on our full stack web development team what i m doing in this document now is trying to provide the complete view angle of modern web app or page development ruled by javascript reflect technological advance and help developers to acquire apis libraries tools services best practices and learning resource which are not outdated and most commonly used i hope this document can help one developer to have more power to do much more and much better just like a spellbook does in fantasy worlds the js web technology is like an ocean of stuff you don t know https medium com javascript scene why im thankful for js fatigue i know you re sick of those words but this is different 296fae0c888f simply collecting more stuff or composing dozens of awesome lists into a single one will only exacerbate the javascript fatigue https medium com ericclemmons javascript fatigue 48d4011b6fc4 so this document must stay lean and focus on the most frequent problems and the most commonly used stuff so for each problem domain and each technology i try my best to pick only one or a few links which link belongs to not outdated and most commonly used stuff is not only decided by clear trends empirical observation and working experience also by public data and web scraping scripts the npm package statistics like download count are given more weight than github repo statistics like starring data because npm statistics can better reflect the actual usage and popularity prefer fine grained classifications and deep hierarchies over featureless descriptions and distractive comments ideally each line is a unique category the symbol between the links means they are replaceable the symbol between the links means they are complementary i wish this document could be closer to a kind of knowledge graph or skill tree than a list or a collection it currently contains 2000 links projects tools plugins services articles books sites etc feel free to submit the missing or better links in your opinion also please provide the reason why not add a europe or other regions section https github com dexteryy spellbook of modern webdev pull 4 issuecomment 308073026 why not add your project https github com dexteryy spellbook of modern webdev pull 5 why so many react based projects why not angular vue js xxx http www npmtrends com rxjs vs mobx vs redux vs vue vs react vs angular core vs cycle dom vs backbone vs jquery vs vuex understanding modern web development in english coming soon in chinese slides https speakerdeck com dexteryy understanding modern web development at jsconf china 2017 zhong wen jsconf cn 2017 http 2017 jsconf cn schedule br br div align center img src assets showme jpg width div br br table of contents platforms and languages platforms and languages open web platform open web platform learning reference visual tools performance security semantics seo accessibility html5 web apis html5 web apis html dom appearance interaction access network media graphics computing css features css features rwd layout typography text animation effects modern css next gen css modern css next gen css css module postcss css in js best practices skeleton methodology code style know more about web design ui design ux design rwd atomic design motion design grid system typography style guide modern js next gen js modern js next gen js es6 features intro to es6 re intro to js important proposals functional programming frp static typing code style webassembly webassembly concepts features rust node js nodejs intro workshop best practices platform compatibility and proposal status platform compatibility and proposal status platform status releases updates ecmascript compatibility proposal status w3c wg wicg whatwg ecma tc39 node js ctc js engine v8 jsc chakra web js runtime electron cordova react native device cross browser polyfill libraries cross browser polyfill libraries appearance interaction access network performance offline media npm ecosystem npm ecosystem finding packages search stats rank dependency management release maintenance npm yarn lerna ncp convention open source semver package json small modules isomorphic js universal js universal utility libraries universal utility libraries standard library extensions fp oop async hashing generating parsing manipulating url validator i18n date numbers color text buffer blob logic network storage nlp ml universal web apps web pages universal web apps web pages gui framework gui framework view viewmodel viewcontroller react model app state redux api graphql gui architectures mvc mvp pm mvvm flux redux elm mvi sam ui toolkits ui toolkits css react standalone ui components standalone ui components layout icon button form overlay picker content editor client side client side ux libraries ux libraries drag drop gesture scrolling zoom tooltip tour graphic libraries graphic libraries animation effects loading scrolling parallax transition timeline motion curved path 2d canvas svg physics 3d webgl physics data visualization game hybrid libraries hybrid libraries electron react native server side server side network network http intro same origin policy performance https http 2 grpc tcp udp server side best practices server side best practices restful api saas microservices api gateway serverless cloud distributed web hosting non distributed authentication authorization security logging monitoring devops microservices api services node js microservices api services nodejs frameworks restful api microservices serverless bots graphql docgen codegen server side libraries node js server side libraries nodejs configuration debugging protocols network crypto auth storage jobs scraping images parsing generating nlp cloud services global cloud services global compute faas serverless webhook paas caas storage object storage dbaas baas crud auth search email sms aiaas bdaas natural language computer vision cloud services china cloud services china the evil twins inside the great firewall of china https github com dexteryy spellbook of modern webdev pull 4 tooling tooling testing testing unit testing test runner test doubles web testing integration testing functional e2e testing visual testing monkey testing headless browsers server side testing functional testing load testing benchmark testing analysis code coverage node js security documentation documentation js api cli css style guide writing toolchain toolchain compiler transpiler preprocessor babel postcss loader builder bundler webpack rollup minifier compressor optimizer prepack babili uglify imagemin cssnano clean css formatter prettier stylefmt static analysis eslint flow stylelint task automation npm scripts gulp workflow workflow development micro generator live reload watch preview dev tools http inspector debugging proxy deployment process supervisor containers container clusters paas monitoring error tracking logging apm command line environment mac command line environment mac terminal homebrew zsh vim git docker dotfiles utilities command line libraries node js command line libraries nodejs input options arguments parser interactive configuration output color style icon updating log notice columns curses drawing delivery os api parser ide editors ide editors vscode plugins ui formatting operating static analysis docs assistant integration atom plugins ui formatting operating static analysis docs assistant integration out of the box atom ide other electron based ide programming fonts useful apps useful apps playground visual tools viewer docs automation collaboration collaboration version control chatops kanban markdown design a subset as a learning path 1 open web platform open web platform 2 html5 web apis html5 web apis 3 css features css features 4 modern css next gen css modern css next gen css 5 modern js next gen js modern js next gen js 6 platform compatibility and proposal status platform compatibility and proposal status 7 network network 8 node js nodejs 9 npm ecosystem npm ecosystem 10 command line environment mac command line environment mac 11 ide editors ide editors 12 gui framework gui framework 13 microservices api services node js microservices api services nodejs 15 testing testing a subset for finding libraries cross browser polyfill libraries cross browser polyfill libraries hybrid libraries hybrid libraries gui framework gui framework ui toolkits ui toolkits standalone ui components standalone ui components ux libraries ux libraries graphic libraries graphic libraries universal utility libraries universal utility libraries microservices api services node js microservices api services nodejs server side libraries node js server side libraries nodejs command line libraries node js command line libraries nodejs a subset for architecture and infrastructure gui framework gui framework toolchain toolchain workflow workflow microservices api services node js microservices api services nodejs server side best practices server side best practices cloud services global cloud services global cloud services china cloud services china documentation documentation br br div align center img src assets merlins spell book jpg width div br br platforms and languages open web platform learning what is the internet http www 20thingsilearned com en us what is the internet how does the internet work https www w3 org wiki how does the internet work http see server side network network evolution of the web http www evolutionoftheweb com timeline of web browsers https en wikipedia org wiki timeline of web browsers dive into html5 a quite biased history of html5 http diveintohtml5 info past html 20 things i learned about browsers and the web http www 20thingsilearned com mdn s learn web development https developer mozilla org en us docs learn reference mdn web docs https developer mozilla org en us docs web html https developer mozilla org en us docs web html reference svg https developer mozilla org en us docs web svg css https developer mozilla org en us docs web css reference dom https developer mozilla org en us docs web api document object model dom events https developer mozilla org en us docs web events web apis https developer mozilla org en us docs web api mdn content roadmap https trello com b lfl3umox mdn content roadmap google developers https developers google com web web fundamentals https developers google com web fundamentals update https developers google com web updates html5rocks archived tutorials https www html5rocks com en tutorials apple webkit js https developer apple com reference webkitjs cssdb https cssdb org css tricks s css almanac https css tricks com almanac codrops css reference https tympanus net codrops css reference mastering css principles a comprehensive guide https www smashingmagazine com mastering css principles comprehensive reference guide html the living standard web developer edition https developers whatwg org the web platform browser technologies https platform html5 org w3fools http www w3fools com w3schools responds to w3fools https readwrite com 2011 01 17 w3schools responds to w3fools why shouldn t i use w3schools https codereview meta stackexchange com questions 4975 why shouldnt i use w3schools as reference why do people hate w3schools https www quora com why do people hate w3schools com does w3schools really suck https www quora com does w3schools really suck visual tools see tooling useful apps useful apps visual tools performance rendering how browsers work behind the scenes of modern web browsers https www html5rocks com en tutorials internals howbrowserswork how browsers lay out web pages https dbaron org talks 2012 03 11 sxsw master xhtml rendering performance https developers google com web fundamentals performance rendering gpu animation doing it right https www smashingmagazine com 2016 12 gpu animation doing it right an introduction to hardware acceleration with css animations https www sitepoint com introduction to hardware acceleration css animations css will change https developer mozilla org en us docs web css will change everything you need to know about the css will change property https dev opera com articles css will change property css containment in chrome 52 https developers google com web updates 2016 06 css containment loading how dns works https howdns works network resilience https web dev reliable evolution of script loading https www stevesouders com blog 2010 12 06 evolution of script loading browser script loading roundup https www stevesouders com blog 2010 02 07 browser script loading roundup javascript start up performance https medium com reloading javascript start up performance 69200f43b201 critical rendering path https developers google com web fundamentals performance critical rendering path css and the critical path http www phpied com css and the critical path offline see html5 web apis html5 web apis offline measure performance budgets 101 https web dev performance budgets 101 measure performance with the rail model https developers google com web fundamentals performance rail measuring page load speed with navigation timing https www html5rocks com en tutorials webperformance basics measuring network performance with resource timing api https developers googleblog com 2013 12 measuring network performance with html user timing api https www html5rocks com en tutorials webperformance usertiming why web developers need to care about interactivity https philipwalton com articles why web developers need to care about interactivity requestidlecallback https developers google com web updates 2015 08 using requestidlecallback performanceobserver https developer mozilla org en us docs web api performanceobserver optimization fast load times https web dev fast why performance matters https developers google com web fundamentals performance why performance matters performance audits https web dev lighthouse performance lighthouse audit references https developers google com web tools lighthouse audits critical request chains security safe and secure https web dev secure the tangled web a guide to securing modern web applications http lcamtuf coredump cx tangled html5 security cheatsheet https html5sec org semantics seo let s talk about semantics http html5doctor com lets talk about semantics easily discoverable https web dev discoverable seo audits https web dev lighthouse seo seo tutorial for beginners https www hobo web co uk seo tutorial google s search engine optimization starter guide http www google com webmasters docs search engine optimization starter guide pdf accessibility accessible to all https web dev accessible the a11y project http a11yproject com using aria https w3c github io using aria return to table of contents table of contents html5 web apis html dom you might not need jquery http youmightnotneedjquery com you don t need jquery https github com oneuijs you dont need jquery now more than ever you might not need jquery https css tricks com now ever might not need jquery head https github com joshbuchea head favicon https github com audreyr favicon cheat sheet form pseudo element https gist github com webtobesocial aefd6e25064c08e0cc9a native form elements http nativeformelements com detect dom changes with mutation observers https developers google com web updates 2012 02 detect dom changes with mutation observers appearance web components https developers google com web updates 2017 01 webcomponents org shadow dom v1 https developers google com web fundamentals getting started primers shadowdom custom elements v1 https developers google com web fundamentals getting started primers customelements web animations https developer mozilla org en us docs web api web animations api web animation past present and future https alistapart com article web animation past present and future let s talk about the web animations api http danielcwilson com blog 2015 07 animations intro status are we animated yet https birtles github io areweanimatedyet interaction desktop mouseevent https developer mozilla org en us docs web api mouseevent wheelevent https developer mozilla org en us docs web api wheelevent keyboardevent https developer mozilla org en us docs web api keyboardevent drag and drop https developer mozilla org en us docs web api html drag and drop api pointer lock https developer mozilla org en us docs web api pointer lock api mobile touchevent https developer mozilla org en us docs web api touchevent 300ms tap delay gone away https developers google com web updates 2013 12 300ms tap delay gone away more responsive tapping on ios https webkit org blog 5610 more responsive tapping on ios deviceorientationevent devicemotionevent https developer mozilla org en us docs web api detecting device orientation hardware agnostic pointerevent https developer mozilla org en us docs web api pointerevent selection https developer mozilla org en us docs web api selection intersection observer api https developer mozilla org en us docs web api intersection observer api intro https developers google com web updates 2016 04 intersectionobserver resize observer api https developers google com web updates 2016 10 resizeobserver gamepad https developer mozilla org en us docs web api gamepad api web speech https developer mozilla org en us docs web api web speech api access url https developer mozilla org en us docs web api url history https developer mozilla org en us docs web api history navigator https developer mozilla org en us docs web api navigator screen https developer mozilla org en us docs web api screen page visibility https developer mozilla org en us docs web api page visibility api clipboard https developer mozilla org en us docs tag clipboard 20api performance https developer mozilla org en us docs web api performance console https developer mozilla org en us docs web api console permissions https developer mozilla org en us docs web api permissions api geolocation https developer mozilla org en us docs web api geolocation web notifications https developer mozilla org en us docs web api notifications api vibration https developer mozilla org en us docs web api vibration api network xmlhttprequest2 https developer mozilla org en us docs web api xmlhttprequest fetch https developer mozilla org en us docs web api fetch api abortable fetch https developers google com web updates 2017 09 abortable fetch why i won t be using fetch api in my apps https medium com shahata why i wont be using fetch api in my apps 6900e6c6fe78 websocket https developer mozilla org en us docs web api websocket server sent event https developer mozilla org en us docs web api eventsource webrtc https developer mozilla org en us docs web api webrtc api getting started with webrtc https www html5rocks com en tutorials webrtc basics webrtc in the real world stun turn and signaling https www html5rocks com en tutorials webrtc infrastructure webrtc data channels https www html5rocks com en tutorials webrtc datachannels workshop codelabs real time communication with webrtc https codelabs developers google com codelabs webrtc web offline overview offline ux considerations https developers google com web fundamentals instant and offline offline ux the offline cookbook https jakearchibald com 2014 offline cookbook offline first html5 technologies for a faster smarter more engaging web http www webdirections org offlineworkshop ibooksdraft pdf web storage https developer mozilla org en us docs web api web storage api indexeddb https developer mozilla org en us docs web api indexeddb api database connection filereader https developer mozilla org en us docs web api filereader file https developer mozilla org en us docs web api file blob https developer mozilla org en us docs web api blob service worker https developer mozilla org en us docs web api service worker api service workers explained https github com w3c serviceworker blob master explainer md service workers an introduction https developers google com web fundamentals getting started primers service workers the service worker lifecycle https developers google com web fundamentals instant and offline service worker lifecycle instant loading web apps with an application shell architecture https developers google com web updates 2015 11 app shell service worker cookbook https serviceworke rs status is serviceworker ready https jakearchibald github io isserviceworkerready progressive web apps https developers google com web progressive web apps progressive web app checklist https developers google com web progressive web apps checklist pwa audits https web dev lighthouse pwa offline storage for progressive web apps https developers google com web fundamentals instant and offline web storage offline for pwa the prpl pattern https developers google com web fundamentals performance prpl pattern workshop codelabs your first progressive web app https codelabs developers google com codelabs your first pwapp media video https developer mozilla org en us docs web html element video audio https developer mozilla org en us docs web html element audio web audio api https developer mozilla org en us docs web api web audio api web audio api book http chimera labs oreilly com books 1234000001552 index html workshop web audio school https github com mmckegg web audio school media streams https developer mozilla org en us docs web api media streams api capturing audio video in html5 https www html5rocks com en tutorials getusermedia intro graphics svg https developer mozilla org en us docs web svg styling and animating svgs with css https www smashingmagazine com 2014 11 styling and animating svgs with css canvas https developer mozilla org en us docs html canvas html5 canvas http chimera labs oreilly com books 1234000001654 index html webgl https developer mozilla org en us docs web api webgl api webgl by example https developer mozilla org en us docs learn webgl by example webgl tutorial https developer mozilla org en us docs web api webgl api tutorial learning webgl http learningwebgl com blog page id 1217 primer shaders https notes underscorediscovery com shaders a primer an introduction to shaders https aerotwist com tutorials an introduction to shaders part 1 the book of shaders http thebookofshaders com workshop shader school https github com stackgl shader school webgl workshop https github com stackgl webgl workshop webgl academy http www webglacademy com learning modern 3d graphics programming https paroj github io gltut webxr immersive web https github com immersive web webxr welcome to the immersive web https developers google com web updates 2018 05 welcome to immersive progressive webxr https blog mozvr com progressive webxr ar store computing web cryptography https developer mozilla org en us docs web api crypto web workers https developer mozilla org en us docs web api web workers api webassembly see webassembly webassembly return to table of contents table of contents css features basics you don t need javascript https github com you dont need you dont need javascript css selectors from css4 till css1 http css4 selectors com selectors css diner where we feast on css selectors http flukeout github io an ultimate guide to css pseudo classes and pseudo elements https www smashingmagazine com 2016 05 an ultimate guide to css pseudo classes and pseudo elements supports rule feature queries https www sitepoint com an introduction to css supports rule feature queries houdini https github com w3c css houdini drafts wiki houdini demystifying css https developers google com web updates 2016 05 houdini houdini maybe the most exciting development in css you ve never heard of https www smashingmagazine com 2016 03 houdini maybe the most exciting development in css youve never heard of responsive web design media queries media queries for standard devices https css tricks com snippets css media queries for standard devices images responsive images https developers google com web fundamentals design and ui responsive images responsive images in css https css tricks com responsive images css units font size idea px at the root rem for components em for text elements https css tricks com rems ems understanding and using rem units in css https www sitepoint com understanding and using rem units in css truly fluid typography with vh and vw units https www smashingmagazine com 2016 05 fluid typography layout https developer mozilla org en us docs learn css css layout flexbox css grid layout css grid flexbox and box alignment our new system for web layout https www smashingmagazine com 2016 11 css grids flexbox and box alignment our new system for web layout a complete guide to flexbox css tricks https css tricks com snippets css a guide to flexbox flexbox codrops https tympanus net codrops css reference flexbox using flexbox today https chriswrightdesign com experiments using flexbox today solved by flexbox https philipwalton github io solved by flexbox flexbox patterns http www flexboxpatterns com home centering elements with flexbox https www smashingmagazine com 2013 05 centering elements with flexbox quantity queries with flexbox https www smashingmagazine com 2015 07 quantity ordering with css a complete guide to grid css tricks https css tricks com snippets css complete guide grid a complete guide to css grid codrops https tympanus net codrops css reference grid traditional learn css layout http learnlayout com learn css layout the pedantic way http book mixu net css css floats 101 https alistapart com article css floats 101 all about floats https css tricks com all about floats css float theory things you should know https www smashingmagazine com 2007 05 css float theory things you should know css positioning 101 https alistapart com article css positioning 101 css position sticky introduction and polyfills https www sitepoint com css position sticky introduction polyfills the z index css property a comprehensive look https www smashingmagazine com 2009 09 the z index css property a comprehensive look centering in css a complete guide https css tricks com centering css complete guide absolute center an image https css tricks com snippets css absolute center vertical horizontal an image how to center in css http howtocenterincss com web typography using font face https css tricks com snippets css using font face a comprehensive guide to font loading strategies https www zachleat com web comprehensive webfonts text handling long words and urls https css tricks com snippets css prevent long urls from breaking out of container writing mode https developer mozilla org en us docs web css writing mode text orientation https developer mozilla org en us docs web css text orientation animation css transition using css transitions https developer mozilla org en us docs web css css transitions using css transitions intro to css 3d transforms http desandro github io 3dtransforms css animation the guide to css animation principles and examples https www smashingmagazine com 2011 09 the guide to css animation principles and examples upgrading css animation with motion curves https www smashingmagazine com 2016 08 css animations motion curves motion path animating clipped elements in svg https www smashingmagazine com 2015 12 animating clipped elements svg moving along a curved path in css with layered animation http tobiasahlin com blog curved path animations in css future use css motion paths https codepen io danwilson post css motion paths effects css image effects https una im vintage washout web image effects performance showdown https www smashingmagazine com 2016 05 web image effects performance showdown basics of css blend modes https css tricks com basics css blend modes css blend modes could be the next big thing in web design https medium com bennettfeely css blend modes could be the next big thing in web design 6b51bf53743a understanding css filter effects https www html5rocks com en tutorials filters understanding css clipping and masking in css https css tricks com clipping masking css the state of css reflections https css tricks com state css reflections css shapes 101 https alistapart com article css shapes 101 return to table of contents table of contents modern css next gen css component based css utility class functional css utility first css atomic css the case for atomic utility first css https johnpolacek github io the case for atomic css css utility classes and separation of concerns https adamwathan me css utility classes and separation of concerns a year of utility classes https css irl info a year of utility classes so you need a css utility library https css tricks com need css utility library see ui toolkits ui toolkits css modules https github com css modules css modules the end of global css https medium com seek blog the end of global css 90d2a4a06284 tools see tooling toolchain toolchain builder bundler webpack styled components https github com styled components styled components emotion https emotion sh css in js https speakerdeck com vjeux react css in js a unified styling language https medium com seek blog a unified styling language d0c208de2660 a brief history of css in js how we got here and where we re going https levelup gitconnected com a brief history of css in js how we got here and where were going ea6261c19f04 the state of css http ryanogles by css javascript 2017 05 25 the state of css html comparison of css in js solutions http michelebertoli github io css in js styled components enforcing best practices in component based systems https www smashingmagazine com 2017 01 styled components enforcing best practices component based systems writing your styles in js writing inline styles http mxstbr blog 2016 11 inline styles vs css in js libraries styled system https github com jxnblk styled system system components https github com jxnblk styled system tree master system components grid styled https jxnblk com grid styled styled normalize https github com sergeysova styled normalize styled sanitize https www npmjs com package styled sanitize styled components breakpoint https github com jameslnewell styled components breakpoint styled tools https github com diegohaz styled tools preprocessor based css postcss http postcss org intro meet postcss http www meetpostcss com postcss a comprehensive introduction https www smashingmagazine com 2015 12 introduction to postcss postcss sass killer or preprocessing pretender https ashleynolan co uk blog postcss a review postcss playground https sneakertack github io postcss playground preset env https preset env cssdb org features it s time to start using css custom properties https www smashingmagazine com 2017 04 start using css custom properties getting started with css calc https www smashingmagazine com 2015 12 getting started css calc techniques more plugins see tooling toolchain toolchain compiler transpiler preprocessor postcss best practices sanitize css https github com csstools sanitize css normalize css http nicolasgallagher com about normalize css reset css http meyerweb com eric tools css reset methodology bem https en bem info methodology bem 101 https css tricks com bem 101 mindbemding https csswizardry com 2013 01 mindbemding getting your head round bem syntax oocss https github com stubbornella oocss wiki an introduction to object oriented css oocss https www smashingmagazine com 2011 12 an introduction to object oriented css oocss smacss https smacss com itcss https www xfive co blog itcss scalable maintainable css architecture rscss http rscss io solid css http blog millermedeiros com solid css css guidelines https cssguidelin es maintainablecss https maintainablecss com code style idiomatic css https github com necolas idiomatic css airbnb css sass styleguide https github com airbnb css airbnb css in javascript style guide https github com airbnb javascript tree master css in javascript css html isobar front end code standards http isobar idev github io code standards code guide by mdo http codeguide co know more about web design ui design ux design https medium com mockplus ux vs ui vs ia vs ixd 4 confusing digital design terms defined ebd679f53f2 responsive adaptive web design responsive web design basics https developers google com web fundamentals design and ui responsive responsive web design what it is and how to use it https www smashingmagazine com 2011 01 guidelines for responsive web design the difference between responsive and adaptive design https css tricks com the difference between responsive and adaptive design the current state of adaptive design https medium com swlh the current state of adaptive design 6b2b89b258c4 responsivedesign is design https responsivedesign is design develop https responsivedesign is develop patterns responsive web design patterns https developers google com web fundamentals design and ui responsive patterns responsive patterns http bradfrost github io this is responsive patterns html responsivedesign is patterns https responsivedesign is patterns responsive data table roundup https css tricks com responsive data table roundup motion design creating usability with motion the ux in motion manifesto https medium com ux in motion creating usability with motion the ux in motion manifesto a87a4584ddc 10 principles for smooth web animations https blog gyrosco pe smooth css animations 7d8ffc2c1d29 grid system a comprehensive introduction to grids in web design https webdesign tutsplus com articles a comprehensive introduction to grids in web design cms 26521 calc grid system lost grid http lostgrid org flexbox grid system flexbox grid http flexboxgrid com the 8 point grid https spec fm specifics 8 pt grid typography typography js https www npmjs com package typography gutenberg http matejlatin github io gutenberg the equilateral triangle of a perfect paragraph https betterwebtype com triangle the elements of typographic style applied to the web http webtypography net toc why is vertical rhythm an important typography practice https zellwk com blog why vertical rhythms css with vertical rhythm https drewish com tools vertical rhythm more meaningful typography https alistapart com article more meaningful typography modular scale http www modularscale com atomic design http bradfrost com blog post atomic web design book http atomicdesign bradfrost com table of contents the atomic workflow people process and making design systems happen https www smashingmagazine com atomic design workflow the other interface atomic design with sass https www smashingmagazine com 2013 08 other interface atomic design sass atomic design your ultimate guide to scalable modular css sass https blog alexdevero com atomic design scalable modular css sass design system a comprehensive guide to design systems https www invisionapp com blog guide to design systems design systems handbook https www designbetter co design systems handbook introducing design systems design tokens tokens in design systems https medium com eightshapes llc tokens in design systems 25dd82d58421 how to manage your design tokens with style dictionary https medium com didoo how to manage your design tokens with style dictionary 98c795b938aa what are design tokens https css tricks com what are design tokens style guide style guide driven development living style guides http styleguides io tools see tooling documentation documentation style guide examples apple s human interface guidelines https developer apple com design google s material design https material io microsoft s fluent design system http fluent microsoft com airbnb s new design system https airbnb design building a visual language github s primer http primercss io atlassian s design guidelines https atlassian design guidelines product overview salesforce s lightning design system https www lightningdesignsystem com yelp s styleguide https www yelp com styleguide ibm s living language https www ibm com design language bbc s gel guidelines http www bbc co uk gel guidelines a list apart s pattern library http patterns alistapart com span usa span gov s web design standards https standards usa gov mailchimp s email design guide https mailchimp com email design guide return to table of contents table of contents modern js next gen js es6 features overview of ecmascript 6 features https github com lukehoban es6features babel repl http babeljs io repl es6 new features comparison http es6 features org intro to es6 dr axel rauschmayer s blog http 2ality com exploring es6 http exploringjs com es6 exploring es2016 and es2017 http exploringjs com es2016 es2017 es6 in depth https hacks mozilla org category es6 in depth nicholas c zakas s understanding ecmascript 6 https leanpub com understandinges6 re intro to js articles mdn a re introduction to javascript js tutorial https developer mozilla org en us docs web javascript a re introduction to javascript equality comparisons and sameness https developer mozilla org en us docs web javascript equality comparisons and sameness data types and data structures https developer mozilla org en us docs web javascript data structures closures https developer mozilla org en us docs web javascript closures inheritance and the prototype chain https developer mozilla org en us docs web javascript inheritance and the prototype chain concurrency model and event loop https developer mozilla org en us docs web javascript eventloop memory management https developer mozilla org en us docs web javascript memory management dmitry soshnikov javascript the core http dmitrysoshnikov com ecmascript javascript the core ecma 262 3 in detail execution contexts http dmitrysoshnikov com ecmascript chapter 1 execution contexts variable object http dmitrysoshnikov com ecmascript chapter 2 variable object this http dmitrysoshnikov com ecmascript chapter 3 this scope chain http dmitrysoshnikov com ecmascript chapter 4 scope chain functions http dmitrysoshnikov com ecmascript chapter 5 functions closures http dmitrysoshnikov com ecmascript chapter 6 closures evaluation strategy http dmitrysoshnikov com ecmascript chapter 8 evaluation strategy oop the general theory http dmitrysoshnikov com ecmascript chapter 7 1 oop general theory ecmascript implementation http dmitrysoshnikov com ecmascript chapter 7 2 oop ecmascript implementation ecma 262 5 in detail properties and property descriptors http dmitrysoshnikov com ecmascript es5 chapter 1 properties and property descriptors strict mode http dmitrysoshnikov com ecmascript es5 chapter 2 strict mode lexical environments common theory http dmitrysoshnikov com ecmascript es5 chapter 3 1 lexical environments common theory ecmascript implementation http dmitrysoshnikov com ecmascript es5 chapter 3 2 lexical environments ecmascript implementation notes equality operators http dmitrysoshnikov com notes note 2 ecmascript equality operators default values of parameters http dmitrysoshnikov com ecmascript es6 notes default values of parameters dmitri pavlutin equality operator https dmitripavlutin com the legend of javascript equality operator undefined https dmitripavlutin com 7 tips to handle undefined in javascript variables hoisting https dmitripavlutin com javascript hoisting in details variables lifecycle https dmitripavlutin com variables lifecycle and why let is not hoisted declare functions https dmitripavlutin com 6 ways to declare javascript functions this keyword https dmitripavlutin com gentle explanation of this in javascript three dots https dmitripavlutin com how three dots changed javascript array creation https dmitripavlutin com power up the array creation in javascript object literals https dmitripavlutin com why object literals in javascript are cool well known symbols https dmitripavlutin com detailed overview of well known symbols small and plain functions https dmitripavlutin com the art of writing small and plain functions unicode https dmitripavlutin com what every javascript developer should know about unicode other the evolution of javascript modularity https github com myshov history of javascript tree master 4 evolution of js modularity about object oriented design and the class extends keywords in es6 http blog wolksoftware com about classes inheritance and object oriented design in typescript and es6 javascript regular expression enlightenment http codylindley com techpro 2013 05 14 javascript regular expression books eloquent javascript http eloquentjavascript net speaking javascript http speakingjs com es5 you don t know js book series https github com getify you dont know js reference javascript guide https developer mozilla org en us docs web javascript guide javascript reference https developer mozilla org en us docs web javascript reference important proposals esm ecmascript modules intro the state of javascript modules https medium com webpack the state of javascript modules 4636d1774358 ecmascript 6 modules the final syntax http 2ality com 2014 09 es6 modules final html es6 modules in depth https ponyfoo com articles es6 modules in depth the es6 module system browsers ecmascript modules in browsers https jakearchibald com 2017 es modules in browsers node js node js tc 39 and modules https hackernoon com node js tc 39 and modules a1118aecf95e mjs https nodejs org api esm html using es modules natively in node js http 2ality com 2017 09 native esm node html esm https www npmjs com package esm es modules in node today https medium com web on the edge es modules in node today 32cff914e4b dynamic import import https github com tc39 proposal dynamic import class fields static properties https github com tc39 proposal class public fields issues 46 issuecomment 239031422 decorators https github com wycats javascript decorators async await https github com yortus asyncawait promise https developer mozilla org en docs web javascript reference global objects promise promise promote https www promisejs org promises a https promisesaplus com implementations observables https github com tc39 proposal observable static typing https ecmascript daily github io pages status of static typing in ecmascript concurrent js parallel javascript concurrent javascript it can work https webkit org blog 7846 concurrent javascript it can work the path to parallel javascript https blog mozilla org javascript 2015 02 26 the path to parallel javascript a taste of javascript s new parallel primitives https hacks mozilla org 2016 05 a taste of javascripts new parallel primitives a cartoon intro to arraybuffers and sharedarraybuffers https hacks mozilla org 2017 06 a cartoon intro to arraybuffers and sharedarraybuffers functional programming functional programming for javascript people https medium com chetcorcos functional programming for javascript people 1915d8775504 functional programming jargon https github com hemanth functional programming jargon composing software https medium com javascript scene the rise and fall and rise of functional programming composable software c2d91b424c8c books professor frisby s mostly adequate guide to functional programming https drboolean gitbooks io mostly adequate guide functional light javascript https github com getify functional light js lodash s fp guide https github com lodash lodash wiki fp guide introduction to immutable js and functional programming concepts https auth0 com blog intro to immutable js why ramda http fr umio us why ramda the philosophy of ramda http fr umio us the philosophy of ramda favoring curry http fr umio us favoring curry thinking in ramda http randycoulman com blog 2016 05 24 thinking in ramda getting started fantasy land https github com fantasyland fantasy land from callback to future functor monad https hackernoon com from callback to future functor monad 6c86d9c16cb5 adt algebraic data types http blog jenkster com 2016 06 functional mumbo jumbo adts html javascript and type thinking https medium com yelouafi javascript and type thinking 735edddc388d functors applicatives and monads in pictures http adit io posts 2013 04 17 functors applicatives and monads in pictures html frp functional reactive programming the introduction to reactive programming you ve been missing https gist github com staltz 868e7e9bc2a7b8c1f754 how is reactive different from procedural programming http insights dice com 2014 01 13 how is reactive different from procedural programming a general theory of reactivity https github com kriskowal gtor learn rxjs https www learnrxjs io rx book http xgrommx github io rx book index html functional programming in javascript http reactivex io learnrx rxmarbles http rxmarbles com static typing intro why use static types in javascript https medium freecodecamp com why use static types in javascript part 1 8382da1e0adb you might not need typescript or static types https medium com javascript scene you might not need typescript or static types aa7cb670a77b flow https flow org en docs flow runtime https codemix github io flow runtime flow comments https flow org blog 2015 02 20 flow comments typescript http www typescriptlang org typescript playground https www typescriptlang org play definitelytyped http definitelytyped org typesearch http microsoft github io typesearch tcomb https www npmjs com package tcomb jsdoc tags https github com google closure compiler wiki annotating javascript for the closure compiler jsdoc to assert https github com azu jsdoc to assert concurrent js parallel javascript napa js https github com microsoft napajs code style airbnb javascript style guide https github com airbnb javascript node js style guide https github com felixge node style guide clean code javascript https github com ryanmcdermott clean code javascript javascript clean coding best practices https blog risingstack com javascript clean coding best practices node js at scale return to table of contents table of contents webassembly references webassembly org http webassembly org mdn docs https developer mozilla org en us docs webassembly concepts webassembly high level goals https github com webassembly design blob master highlevelgoals md minimum viable product https github com webassembly design blob master mvp md webassembly concepts https developer mozilla org en us docs webassembly concepts an abridged cartoon introduction to webassembly https www smashingmagazine com 2017 05 abridged cartoon introduction webassembly features features to add after the mvp https github com webassembly design blob master futurefeatures md webassembly proposals https github com webassembly proposals workshop codelabs an introduction to web assembly https codelabs developers google com codelabs web assembly intro languages rust https www rust lang org rust and webassembly https rustwasm github io docs html the rust wasm book https rustwasm github io docs book node js intro the art of node https github com maxogden art of node you don t know node https webapplog com you dont know node risingstack s https blog risingstack com node js at scale understanding node js event loop nodesource s https nodesource com blog understanding the nodejs event loop understanding the node js event loop node js garbage collection explained https blog risingstack com node js at scale node js garbage collection stream handbook https github com substack stream handbook a brief history of node streams https medium com the node js collection a brief history of node streams pt 1 3401db451f21 understanding object streams https nodesource com blog understanding object streams keeping the node js core small https developer ibm com node 2017 04 20 keeping node js core small debugging node js with google chrome https medium com the node js collection debugging node js with google chrome 4965b5f910f4 add v8 inspector supports https medium com paul irish debugging node js nightlies with chrome devtools 7c4a1b95ae27 how to debug node js with the best tools available https blog risingstack com how to debug nodej js with the best tools available workshop nodeschool https nodeschool io learnyounode https www npmjs com package learnyounode best practices the node way http thenodeway io introduction joyent s production practices design https www joyent com node js production design error handling https www joyent com node js production design errors best practices for node js development https devcenter heroku com articles node best practices node js best practices https github com alanjames1987 node js best practices return to table of contents table of contents platform compatibility and proposal status web platform status can i use http caniuse com chrome https www chromestatus com features webkit https webkit org status firefox https platform status mozilla org edge https developer microsoft com en us microsoft edge platform status tbs china http x5 tencent com tbs guide w3c html platform releases chrome https chromereleases googleblog com safari https developer apple com safari whats new webkit https trac webkit org firefox https www mozilla org en us firefox releases edge https developer microsoft com en us microsoft edge platform changelog platform updates mozilla hacks https hacks mozilla org web updates https developers google com web updates chromium blog https blog chromium org webkit blog https webkit org blog microsoft edge dev blog https developer microsoft com en us microsoft edge community writing forward compatible websites https developer mozilla org en us docs web guide writing forward compatible websites polyfill what is a polyfill https remysharp com 2010 10 08 what is a polyfill feature detection modernizr feature detects https github com modernizr modernizr tree master feature detects feature js https github com viljamis feature js blob master feature js browser device runtime detection see platforms and languages universal utility libraries universal utility libraries parsing manipulating graded browser support https github com yui yui3 wiki graded browser support grade components not browsers https www filamentgroup com lab grade the components html email css support guide for email clients https www campaignmonitor com css email client css support https templates mailchimp com resources email client css support email design reference https templates mailchimp com html email templates https github com mailchimp email blueprints node js platform releases node js release working group https github com nodejs release ecmascript support ecmascript compatibility table http kangax github io compat table es6 node js es2015 support http node green node 10 x lts supports es modules natively without experimental modules node 8 5 https nodejs org en blog release v8 5 0 supports es modules natively mjs experimental modules node 8 3 https nodejs org en blog release v8 3 0 v8 6 0 https v8project blogspot hk 2017 04 v8 release 59 html ignition turbofan launched https v8project blogspot hk 2017 05 launching ignition and turbofan html node 8 0 lts https nodejs org en blog release v8 0 0 v8 5 8 https v8project blogspot hk 2017 03 v8 release 58 html five new features you need to know http codingsans com blog node 8 node 7 6 https nodejs org en blog release v7 6 0 v8 5 5 https v8project blogspot hk 2016 10 v8 release 55 html async functions node 6 0 lts https nodejs org en blog release v6 0 0 v8 5 0 https v8project blogspot hk 2016 03 v8 release 50 html 93 of es6 language features performance six speed https kpdecker github io six speed proposal status w3c wg https www w3 org consortium activities working world wide web consortium working groups web platform publication status https www w3 org webplatform wg pubstatus javascript apis https www w3 org standards techs js mobile web applications https www w3 org standards techs mobileapp css https www w3 org standards techs css css current work https www w3 org style css current work current html5 specifications http html5 overview net current inside w3c tr technical reports https www w3 org 2014 process 20140801 rec advance an inside view of the css working group at w3c http fantasai inkedblade net weblog 2011 inside csswg wicg https wicg github io admin charter html web incubator community group proposals https github com wicg whatwg https whatwg org faq web hypertext application technology working group whatwg live standards https spec whatwg org inside w3c vs whatwg html5 specs the differences documented http developer telerik com featured w3c vs whatwg html5 specs differences documented ecma tc39 http ecma international org memento tc39 htm ecma international technical committee 39 status process and documents for ecma262 https github com tc39 ecma262 ecmascript proposals https github com tc39 proposals tc39 proposals https prop tc39 now sh inside the tc39 process http tc39 github io process document the tc39 process for ecmascript features http 2ality com 2015 11 tc39 process html node js tsc https github com nodejs tsc node js foundation technical steering committee meeting notes https github com nodejs tsc tree master meetings inside how node js created a model open source community https readwrite com 2016 04 15 how node js model open source community pl1 healthy open source https medium com the node js collection healthy open source 967fa8be7951 js engine a guide to javascript engines for idiots http developer telerik com featured a guide to javascript engines for idiots v8 https developers google com v8 how the v8 engine works http thibaultlaurens github io javascript 2013 04 29 how the v8 engine works internal v8 a tale of two compilers https wingolog org archives 2011 07 05 v8 a tale of two compilers a tour of v8 full compiler http jayconrod com posts 51 a tour of v8 full compiler a tour of v8 garbage collection http jayconrod com posts 55 a tour of v8 garbage collection next generation ignition turbofan launch and declarative javascript http benediktmeurer de 2017 04 03 v8 behind the scenes march edition launching ignition and turbofan https v8project blogspot hk 2017 05 launching ignition and turbofan html a tale of turbofan http benediktmeurer de 2017 03 01 v8 behind the scenes february edition ignition turbofan and es2015 http benediktmeurer de 2016 11 25 v8 behind the scenes november edition jsc https trac webkit org wiki javascriptcore javascriptcore the webkit js implementation https wingolog org archives 2011 10 28 javascriptcore the webkit js implementation internal introducing the webkit ftl jit https webkit org blog 3362 introducing the webkit ftl jit next generation jsc love es6 https webkit org blog 7536 jsc loves es6 introducing the b3 jit compiler https webkit org blog 5852 introducing the b3 jit compiler chakra https github com microsoft chakracore microsoft edge s javascript engine to go open source https blogs windows com msedgedev 2015 12 05 open source chakra core architecture overview https github com microsoft chakracore wiki architecture overview node chakracore and vm neutrality in node js https blogs windows com msedgedev 2016 11 29 node chakracore vm neutrality internal javascript performance updates 2015 https blogs windows com msedgedev 2015 05 20 delivering fast javascript performance in microsoft edge 2016 https blogs windows com msedgedev 2016 06 22 javascript performance updates anniversary update 2017 https blogs windows com msedgedev 2017 04 20 improved javascript performance webassembly shared memory next generation roadmap https github com microsoft chakracore wiki roadmap spidermonkey https developer mozilla org en us docs mozilla projects spidermonkey the monkeys in 2013 https blog mozilla org javascript 2014 01 23 the monkeys in 2013 benchmarks the truth about traditional javascript benchmarks http benediktmeurer de 2016 12 16 the truth about traditional javascript benchmarks browser benchmarks http browserbench org web runtime js runtime electron https electron atom io tutorials essential electron http jlord us essential electron cordova https cordova apache org platform support https cordova apache org docs en latest guide support index html top mistakes by developers new to cordova phonegap https github com jessemonroy650 top phonegap mistakes blob master new to phonegap md curated plugins awesome cordova plugins https github com rdn87 awesome cordova plugins list plugins finding plugins plugreg http www plugreg com plugin search https cordova apache org plugins react native http facebook github io react native nativescript https www nativescript org weex https weex project io react native styling cheat sheet https github com vhpoet react native styling cheat sheet bridging in react native an in depth look into react native s core https tadeuzagallo com blog react native bridge tutorials react native express http www reactnativeexpress com react native workshop https rangle io gitbooks io react native workshop react native training https unbug gitbooks io react native training content examples 30 days of react native https github com fangwei716 30 days of react native device the ultimate guide to iphone resolutions https www paintcodeapp com news ultimate guide to iphone resolutions device metrics https material io devices screen sizes http screensiz es monitor return to table of contents table of contents cross browser polyfill libraries appearance responsive web design media queries enquire js https www npmjs com package enquire js responsive image picturefill https www npmjs com package picturefill viewport units buggyfill https www npmjs com package viewport units buggyfill web typography font face font face observer https www npmjs com package fontfaceobserver web animation api web animations polyfill https www npmjs com package web animations js web components webcomponents js v1 spec polyfills https github com webcomponents webcomponentsjs polymer https www polymer project org interaction keyboard mousetrap https craig is killing mice scroll behavior smooth smoothscroll polyfill https www npmjs com package smoothscroll polyfill pointerevent pep https www npmjs com package pepjs react pointable https www npmjs com package react pointable resizeobserver polyfill https github com que etc resize observer polyfill access web notifications api push js https www npmjs com package push js notify js https www npmjs com package notifyjs clipboard api clipboard js https www npmjs com package clipboard copy to clipboard https www npmjs com package copy to clipboard fullscreen api screenfull https www npmjs com package screenfull page visibility api visibility js https www npmjs com package visibilityjs iframe iframe resizer https www npmjs com package iframe resizer network xhr window fetch polyfill https github com github fetch server sent events eventsource polyfill https github com amvtek eventsource websocket socket io client https www npmjs com package socket io client engine io client https www npmjs com package engine io client sockjs client https www npmjs com package sockjs client performance web worker greenlet https github com developit greenlet workerize https github com developit workerize document write postscribe https www npmjs com package postscribe user timing api marky https www npmjs com package marky offline service work workbox https developers google com web tools workbox file filereader api filesaver js https www npmjs com package file saver streamsaver js https github com jimmywarting streamsaver js blob util https www npmjs com package blob util indexeddb localstorage api localforage https www npmjs com package localforage media video video js http videojs com audio howler js https howlerjs com web audio api waud js http www waudjs com tone js https tonejs github io return to table of contents table of contents npm ecosystem npm https www npmjs com how many npm users are there http blog npmjs org post 143451680695 how many npm users are there module counts http www modulecounts com why not to use version control hosting for packages http blog npmjs org post 154387331670 the right tool for the job why not to use version npm and front end packaging http blog npmjs org post 101775448305 npm and front end packaging changes to npm s unpublish policy http blog npmjs org post 141905368000 changes to npms unpublish policy kik left pad and npm http blog npmjs org post 141577284765 kik left pad and npm hello yarn http blog npmjs org post 151660845210 hello yarn finding packages search npms io https npms io node modules com http node modules com npmsearch com http npmsearch com improved search in the npm cli and how we got here http blog npmjs org post 156076312840 search update better search is here http blog npmjs org post 154912817335 better search is here github search sort by stars for js https github com search l javascript q stars 3a 3e1 s stars type repositories stats npm trends http www npmtrends com npmcompare https npmcompare com npm stat https npm stat com rank the state of javascript http stateofjs com stack overflow annual developer survey https insights stackoverflow com survey npm s most depended upon packages https www npmjs com browse depended dependency management release maintenance npm developer guide https docs npmjs com misc developers npm s cli https docs npmjs com cli v5 0 0 http blog npmjs org post 161081169345 v500 npm s lockfiles http blog npmjs org post 161627993435 learn more about npms lockfiles yarn https yarnpkg com yarn s cli https yarnpkg com en docs cli yarn lock https yarnpkg com en docs yarn lock lerna https lernajs io semantic release https www npmjs com package semantic release np https www npmjs com package np gh release https www npmjs com package gh release npm check updates https www npmjs com package npm check updates check dependencies https www npmjs com package check dependencies changed log https www npmjs com package changed log license checker https www npmjs com package license checker convention open source readme art of readme https github com noffle art of readme how to write a readme http jfhbrook github io 2011 11 09 readmes html top ten reasons why i won t use your open source project https changelog com posts top ten reasons why i wont use your open source project readme driven development http tom preston werner com 2010 08 23 readme driven development html template common readme https github com noffle common readme standard readme https github com richardlitt standard readme zalando s readme template https github com zalando zalando howto open source blob master readmetemplate md changelog conventional commits https conventionalcommits org conventional changelog https github com conventional changelog conventional changelog how to write a git commit message https chris beams io posts git commit license choose an open source license https choosealicense com semver semver semantic versioning http semver org the semantic versioner for npm https docs npmjs com misc semver semver a primer https nodesource com blog semver a primer npm semver calculator https semver npmjs com package json specifics of npm s package json https docs npmjs com files package json specifics of yarn s package json https yarnpkg com en docs package json what s the difference between dependencies devdependencies and peerdependencies http stackoverflow com questions 18875674 whats the difference between dependencies devdependencies and peerdependencies small modules unix philosophy and node js http blog izs me post 48281998870 unix philosophy and nodejs module best practices https github com mattdesl module best practices how i write modules http substack net how i write modules hyper modular one line modules small focused modules https github com sindresorhus ama issues 10 issuecomment 117766328 hyper modular packages a crazy cult or a reasonable practice http thefullstack xyz hyper modular packages a crazy cult or a reasonable practice in defense of hyper modular javascript https medium freecodecamp com in defense of hyper modular javascript 33934c79e113 isomorphic js universal js isomorphic javascript the future of web apps https medium com airbnb engineering isomorphic javascript the future of web apps 10882b7a2ebc universal javascript https medium com mjackson universal javascript 4761051b7ae9 return to table of contents table of contents universal utility libraries standard library extensions utilities lodash https lodash com is js http is js org fp ramda http ramdajs com ramda fantasy https www npmjs com package ramda fantasy immutable immutability helper https www npmjs com package immutability helper redux immutable state invariant https www npmjs com package redux immutable state invariant redux freeze https www npmjs com package redux freeze icepick https www npmjs com package icepick seamless immutable https www npmjs com package seamless immutable dot prop immutable https www npmjs com package dot prop immutable object path immutable https www npmjs com package object path immutable timm https www npmjs com package timm updeep https www npmjs com package updeep immutablejs http facebook github io immutable js oop lodash decorators https www npmjs com package lodash decorators stampit https www npmjs com package stampit async observable rxjs https www npmjs com package rxjs promise es6 promisify https www npmjs com package es6 promisify bluebird http bluebirdjs com docs features html generator co https www npmjs com package co callback async http caolan github io async concurrent parallel syntax xregexp https www npmjs com package xregexp node js api node libs browser https www npmjs com package node libs browser eventemitter3 https www npmjs com package eventemitter3 debugging debug https www npmjs com package debug pino https www npmjs com package pino hashing generating uuid https www npmjs com package uuid cuid http usecuid org shortid https www npmjs com package shortid punycode https www npmjs com package punycode string hash https www npmjs com package string hash base64 js https www npmjs com package base64 js sha js https www npmjs com package sha js spark md5 https www npmjs com package spark md5 crypto js https www npmjs com package crypto js jsrsasign https www npmjs com package jsrsasign parsing manipulating url url parsing qs https www npmjs com package qs uri js https github com medialize uri js ip address manipulation ip https www npmjs com package ip environment ua sniffing uaparser js https github com faisalman ua parser js useragent https www npmjs com package useragent information platform js https www npmjs com package platform runtime detection is electron renderer https www npmjs com package is electron renderer electron is https www npmjs com package electron is validator string validation validator js https github com chriso validator js schema validation joi https www npmjs com package joi ajv http epoberezkin github io ajv i18n intl js https www npmjs com package intl formatjs https formatjs io guides i18next https www i18next com date date manipulation moment js http momentjs com numbers number manipulation numeral js http numeraljs com money accounting js http openexchangerates github io accounting js color color manipulation chroma js http gka github io chroma js chromatism https www npmjs com package chromatism randomcolor https www npmjs com package randomcolor color extraction node vibrant https www npmjs com package node vibrant colorify js http colorify rocks text text manipulation voca js https vocajs com string js https github com jprichardson string js characters string width https www npmjs com package string width string length https www npmjs com package string length html entities he https www npmjs com package he human readable slug speakingurl https www npmjs com package speakingurl xss sanitizer dompurify https www npmjs com package dompurify xss https www npmjs com package xss http mime types https www npmjs com package mime types content type https www npmjs com package content type json superset serialize javascript https www npmjs com package serialize javascript json5 https www npmjs com package json5 markdown marked https www npmjs com package marked markdown it https www npmjs com package markdown it commonmark http commonmark org a formal spec for github flavored markdown https githubengineering com a formal spec for github markdown links recognition linkify it https www npmjs com package linkify it language detection franc https www npmjs com package franc text differencing diff https www npmjs com package diff json differencing deep diff https www npmjs com package deep diff search fuse js http fusejs io fuzzysearch https www npmjs com package fuzzysearch lunr js https lunrjs com js worker search https www npmjs com package js worker search regexgen https www npmjs com package regexgen escape string regexp https www npmjs com package escape string regexp dsl parser peg js https pegjs org nearley http nearley js org buffer blob type detection file type https www npmjs com package file type image type https www npmjs com package image type size detection probe image size https www npmjs com package probe image size image manipulation jimp https www npmjs com package jimp image crop smartcrop js https www npmjs com package smartcrop qr code barcode qrcode https www npmjs com package qrcode jsbarcode https www npmjs com package jsbarcode logic rate limiter bottleneck https www npmjs com package bottleneck limiter https www npmjs com package limiter network http xhr low level isomorphic fetch https github com matthew andrews isomorphic fetch high level based on xhr axios https www npmjs com package axios based on fetch api hifetch https github com dexteryy project webcube blob master packages hifetch graphql lokka https github com kadirahq lokka tcp mqtt https www npmjs com package mqtt udp p2p simple peer https www npmjs com package simple peer js sip https www npmjs com package jssip webtorrent https www npmjs com package webtorrent storage file database json lowdb https www npmjs com package lowdb indexeddb websql localstorage memory mongodb api nedb https www npmjs com package nedb couchdb api pouchdb https pouchdb com realtime p2p gun https www npmjs com package gun sharedb https www npmjs com package sharedb computation math js http mathjs org simple statistics https simplestatistics org ndarray https www npmjs com package ndarray bignumber js http mikemcl github io bignumber js nlp compromise https github com nlp compromise compromise talisman http yomguithereal github io talisman ml dl tensorflow js https js tensorflow org mljs https www npmjs com package ml synaptic https www npmjs com package synaptic return to table of contents table of contents universal web apps web pages gui framework view viewmodel viewcontroller react https facebook github io react learning pete hunt s react howto https github com petehunt react howto react basic theoretical concepts https github com reactjs react basic under the hood reactjs https bogdan lyashenko github io under the hood reactjs survivejs react https survivejs com react introduction react express http www react express react cheat sheet https reactcheatsheet com best practices react bits https github com vasanthk react bits react in patterns https github com krasimir react in patterns functional ui and components as higher order functions https blog risingstack com functional ui and components as higher order functions next gen what is react fiber 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to clipboard https www npmjs com package react copy to clipboard react cookie https www npmjs com package react cookie use react alone redial https www npmjs com package redial react refetch https www npmjs com package react refetch formik https www npmjs com package formik formsy react https www npmjs com package formsy react lightweight alternative preact https preactjs com inferno https infernojs org angular https angular io vue js https vuejs org cross framework vuera https github com akxcv vuera model app state redux http redux js org learning notes of dan abramov s redux course videos https github com tayiorbeii egghead io redux course notes a cartoon intro to redux https code cartoons com a cartoon intro to redux 3afb775501a6 tic tac toe js redux pattern in plain javascript http ramonvictor github io tic tac toe js reduce boilerplate redux cube https github com dexteryy project webcube tree master packages redux cube author s own project connect react redux https www npmjs com package react redux reselect https www npmjs com package reselect action types action creators reducer switch redux actions https www npmjs com package redux actions flux standard action https www npmjs com package flux standard action topologically combine reducers https www npmjs com package topologically combine reducers asnyc actions redux thunk https www npmjs com package redux thunk redux promise middleware https www npmjs com package redux promise middleware redux debounced https www npmjs com package redux debounced redux observable https www npmjs com package redux observable redux saga https github com redux saga redux saga redux api middleware https www npmjs com package redux api middleware redux axios middleware https www npmjs com package redux axios middleware redux socket io http npmjs com redux socket io redux rest resource https www npmjs com package redux rest resource redux json api https www npmjs com package redux json api redux api https www npmjs com package redux api state normalizr https www npmjs com package normalizr immutalbe see universal utility libraries universal utility libraries standard library extensions fp immutable redux immutable https www npmjs com package redux immutable redux persist https www npmjs com package redux persist redux undo https www npmjs com package redux undo redux reset https www npmjs com package redux reset ui patterns redux form https redux form com react block ui https www npmjs com package react block ui react redux loading bar https www npmjs com package react redux loading bar react notification system redux https www npmjs com package react notification system redux react redux toastr https www npmjs com package react redux toastr redux optimistic ui https www npmjs com package redux optimistic ui app behaviours redux auth wrapper https www npmjs com package redux auth wrapper react intl redux https www npmjs com package react intl redux redux search https www npmjs com package redux search development redux devtools extension https www npmjs com package redux devtools extension redux logger https www npmjs com package redux logger testing see testing testing web testing integration testing mobx https mobx js org baobab https www npmjs com package baobab freezer https www npmjs com package freezer js api data source graphql http graphql org learning queries and mutations http graphql org learn queries playground graphqlhub https www graphqlhub com explore graphql https www graphql com tutorials state management apollo client https www apollographql com client redux source https github com dexteryy project webcube tree master packages redux source author s own project graphql anywhere https www npmjs com package graphql anywhere graphql tools http dev apollodata com tools graphql tools index html offline first learning designing offline first web apps https alistapart com article offline first say hello to offline first http hood ie blog say hello to offline first html offline first and the circle of web http hood ie blog offline first and the circle of web html part ii breaking the circle http hood ie blog offline first and the circle of web part ii breaking the circle html routing react router https reacttraining com react router connected react router https github com supasate connected react router react helmet https www npmjs com package react helmet i18n react intl https github com yahoo react intl react i18next https react i18next com react intl redux https www npmjs com package react intl redux monitoring error capture react ga https www npmjs com package react ga redux segment https www npmjs com package redux segment redux raven middleware https www npmjs com package redux raven middleware raven for redux https www npmjs com package raven for redux redux catch https www npmjs com package redux catch redux beacon https www npmjs com package redux beacon services see tooling workflow workflow monitoring debugging why did you update https www npmjs com package why did you update server side rendering see tooling workflow workflow deployment publishing app static web jamstack https jamstack org see tooling workflow workflow deployment publishing app scaffold boilerplate generator create react app https github com facebookincubator create react app angular cli https cli angular io vue cli https www npmjs com package vue cli next js https github com zeit next js webcube https github com dexteryy project webcube author s own project starter kits recommended by the react team https reactjs org community starter kits html javascript stack from scratch https github com verekia js stack from scratch static site generator gatsby https www gatsbyjs org metalsmith http www metalsmith io hexo https hexo io assemble http assemble io gui architectures comparison scaling isomorphic javascript code https blog nodejitsu com scaling isomorphic javascript code comparison of architecture presentation patterns mvp sc mvp pv pm mvvm and mvc https www codeproject com articles 66585 comparison of architecture presentation patterns m unidirectional user interface architectures https staltz com unidirectional user interface architectures html change and its detection in javascript frameworks http teropa info blog 2015 03 02 change and its detection in javascript frameworks html martin fowler s eaadev https martinfowler com eaadev patterns for large scale javascript application architecture https addyosmani com largescalejavascript mvc a https alexatnet com model view controller mvc in javascript b https developer mozilla org en us apps fundamentals modern web app architecture mvc architecture c https developer chrome com apps app frameworks understanding mvc and mvp for javascript and backbone developers https addyosmani com blog understanding mvc and mvp for javascript and backbone developers understanding mvvm a guide for javascript developers https addyosmani com blog understanding mvvm a guide for javascript developers flux concepts https github com facebook flux tree master examples flux concepts flux in depth overview http facebook github io flux docs in depth overview html redux reinventing flux interview with dan abramov https survivejs com blog redux interview the elm architecture https guide elm lang org architecture mvi model view intent in cycle js https cycle js org model view intent html what developers need to know about mvi model view intent https thenewstack io developers need know mvi model view intent sam state action model http sam js org return to table of contents table of contents ui toolkits css skeleton css http getskeleton com tachyons http tachyons io bulma http bulma io material components for the web https github com material components material components web weui https github com weui weui mjml https mjml io foundation for emails 2 http foundation zurb com emails html react reactstrap https reactstrap github io react bootstrap https www npmjs com package react bootstrap material ui http www material ui com react toolbox http react toolbox com ant design https ant design ant design mobile https mobile ant design rebass http jxnblk com rebass blueprint http blueprintjs com semantic ui react https react semantic ui com react foundation https react foundation react weui https weui github io react weui docs react desktop http reactdesktop js org react native web https www npmjs com package react native web return to table of contents table of contents standalone ui components layout grid react flexbox grid http roylee0704 github io react flexbox grid masonry react masonry component https www npmjs com package react masonry component masonry layout https www npmjs com package masonry layout bricks js https www npmjs com package bricks js justified layout http flickr github io justified layout split react split pane https www npmjs com package react split pane split js http nathancahill github io split js dashboard react grid layout https www npmjs com package react grid layout icon react icons https www npmjs com package react icons material design icons http google github io material design icons bytesize icons https www npmjs com package bytesize icons progress react redux loading bar https www npmjs com package react redux loading bar nprogress https www npmjs com package nprogress button buttons http unicorn ui com buttons indicators react ladda https www npmjs com package react ladda ladda http lab hakim se ladda react progress button https www npmjs com package react progress button accordion react collapse https www npmjs com package react collapse react sanfona https www npmjs com package react sanfona picker react tabs https www npmjs com package react tabs react select http jedwatson github io react select react radio group https www npmjs com package react radio group rc slider https www npmjs com package rc slider react slider https www npmjs com package react slider react input range https www npmjs com package react input range react color http casesandberg github io react color react dates https www npmjs com package react dates react datepicker https hacker0x01 github io react datepicker react day picker http react day picker js org pikaday https www npmjs com package pikaday react datetime https www npmjs com package react datetime input react toggle https www npmjs com package react toggle react input autosize https www npmjs com package react input autosize react textarea autosize https www npmjs com package react textarea autosize react tag input https www npmjs com package react tagsinput react autosuggest https www npmjs com package react autosuggest auto formatting react maskedinput https www npmjs com package react maskedinput react text mask https www npmjs com package react text mask cleave js https www npmjs com package cleave js form react json schema form https www npmjs com package react jsonschema form overlay react modal https www npmjs com package react modal sweetalert2 https www npmjs com package sweetalert2 vex https www npmjs com package vex js react overlays https www npmjs com package react overlays react notification system https github com igorprado react notification system react notification system redux https www npmjs com package react notification system redux react redux toastr https www npmjs com package react redux toastr react notification https www npmjs com package react notification react salert https www npmjs com package react s alert notie https www npmjs com package notie drawer react burger menu http negomi github io react burger menu react sidebar https www npmjs com package react sidebar react dock https www npmjs com package react dock react contextmenu https www npmjs com package react contextmenu react block ui https availity github io react block ui content carousel react slick https www npmjs com package react slick nuka carousel https www npmjs com package nuka carousel react paginate https www npmjs com package react paginate react rating https www npmjs com package react rating list table react virtualized https www npmjs com package react virtualized react table https www npmjs com package react table react list https www npmjs com package react list spreadsheet react data grid http adazzle github io react data grid react handsontable https www npmjs com package react handsontable react datasheet https nadbm github io react datasheet treeview react treebeard https www npmjs com package react treebeard react treeview https www npmjs com package react treeview json viewer react json tree https www npmjs com package react json tree react qr code https www npmjs com package qrcode react email table oy vey https www npmjs com package oy vey editor draft js https draftjs org awesome draft js https github com nikgraf awesome draft js slate https github com ianstormtaylor slate react quill https www npmjs com package react quill quill https quilljs com react monaco editor https www npmjs com package react monaco editor react ace https www npmjs com package react ace react codemirror https www npmjs com package react codemirror monaco editor https microsoft github io monaco editor ace https ace c9 io codemirror https codemirror net react markdown https www npmjs com package react markdown react syntax highlighter https www npmjs com package react syntax highlighter highlight js https www npmjs com package highlight js widget react music https github com formidablelabs react music react big calendar https www npmjs com package react big calendar react image gallery https www npmjs com package react image gallery react google maps https www npmjs com package react google maps google map react https www npmjs com package google map react react map gl https www npmjs com package react map gl react youtube https www npmjs com package react youtube react player https www npmjs com package react player searchkit http www searchkit co redux auth https github com lynndylanhurley redux auth surveyjs http surveyjs org return to table of contents table of contents client side ux libraries drag drop react dnd https react dnd github io react dnd react draggable https www npmjs com package react draggable react sortable hoc https www npmjs com package react sortable hoc sortable https github com rubaxa sortable react dropzone https www npmjs com package react dropzone dropzonejs http www dropzonejs com gsap draggable https greensock com draggable gesture hammer js http hammerjs github io interact js http interactjs io zingtouch https zingchart github io zingtouch alloyfinger https github com alloyteam alloyfinger gestures patterns https material io guidelines patterns gestures html react hammerjs https www npmjs com package react hammerjs react swipeable views https github com oliviertassinari react swipeable views react swipeable https www npmjs com package react swipeable swiper http idangero us swiper scrolling viewport and elements react waypoint https www npmjs com package react waypoint waypoints https www npmjs com package waypoints react scrollmonitor https www npmjs com package scrollmonitor react scrollmonitor https www npmjs com package scrollmonitor react visibility sensor https www npmjs com package react visibility sensor react sticky https www npmjs com package react sticky react headroom https www npmjs com package react headroom headroom js https www npmjs com package headroom js react infinite scroller https www npmjs com package react infinite scroller react infinite https www npmjs com package react infinite react lazyload https www npmjs com package react lazyload react pull to refresh https www npmjs com package react pull to refresh smooth scrolling react scroll https www npmjs com package react scroll scrollable react iscroll https www npmjs com package react iscroll iscroll http iscrolljs com zynga scroller http zynga github io scroller scrollable container react custom scrollbars https www npmjs com package react custom scrollbars react scroll box https www npmjs com package react scroll box react scrollbar https www npmjs com package react scrollbar overthrow https www npmjs com package fg overthrow zoom image loupe drift https www npmjs com package drift zoom react image magnify https www npmjs com package react image magnify image viewer react images https www npmjs com package react images react image lightbox https www npmjs com package react image lightbox lightgallery https www npmjs com package lightgallery js smartphoto https www npmjs com package smartphoto crop react avatar editor https www npmjs com package react avatar editor react image crop https www npmjs com package react image crop react cropper https www npmjs com package react cropper resize react resizable https www npmjs com package react resizable react rnd https www npmjs com package react rnd tooltip hint css http kushagragour in lab hint react tether https www npmjs com package react tether tether js http tether io popper js https popper js org react tooltip https www npmjs com package react tooltip tether tooltip http github hubspot com tooltip docs welcome tippy js https atomiks github io tippyjs tour react joyride https www npmjs com package react joyride intro js http introjs com tether shepherd https www npmjs com package tether shepherd chardin js https www npmjs com package chardin js accessiblity react hotkeys https www npmjs com package react hotkeys react a11y https www npmjs com package react a11y return to table of contents table of contents graphic libraries animation effects animate css https daneden github io animate css magic animations https minimamente com example magic animations all animation css3 http all animation github io motion css http pavlyukpetr com awesome effeckt css http h5bp github io effeckt css css3 animation cheat sheet http justinaguilar com animations index html react animations https www npmjs com package react animations animate components https www npmjs com package animate components rc animate https www npmjs com package rc animate hover css http ianlunn github io hover transformicons http www transformicons com hamburgers https www npmjs com package hamburgers loading loaders css https connoratherton com loaders spinkit https github com tobiasahlin spinkit spin js http spin js org react spinkit https www npmjs com package react spinkit react loaders https www npmjs com package react loaders halogen http madscript com halogen react spinjs https www npmjs com package react spinjs queue react flip move https www npmjs com package react flip move rc queue anim https www npmjs com package rc queue anim characters react typist https www npmjs com package react typist rc texty https www npmjs com package rc texty react countup https www npmjs com package react countup countup js https www npmjs com package countup js parallax scrolling scrollreveal js https www npmjs com package scrollreveal scrollmagic http scrollmagic io rellax https www npmjs com package rellax rc scroll anim https www npmjs com package rc scroll anim react springy parallax https www npmjs com package react springy parallax orientation parallax https www npmjs com package parallax js easing d3 ease https www npmjs com package d3 ease tween functions https www npmjs com package tween functions bezier easing https www npmjs com package bezier easing keyframe transition style velocity js http velocityjs org velocity react https www npmjs com package velocity react dynamics js http dynamicsjs com react overdrive https www npmjs com package react overdrive anything anime js http anime js com documentation react anime https www npmjs com package react anime between shapes flubber https www npmjs com package flubber lightweight tweening engine shifty https www npmjs com package shifty tween js https github com tweenjs tween js gsap tweenlite https greensock com tweenlite gsap tweenmax https greensock com tweenmax keyframe timeline style react motion https www npmjs com package react motion react motion ui pack https www npmjs com package react motion ui pack react router transition https www npmjs com package react router transition anything react move https react move js org gsap timelinelite https greensock com timelinelite gsap timelinemax https greensock com timelinemax react gsap enhancer https www npmjs com package react gsap enhancer motion curved path svg vivus http maxwellito github io vivus shape mo js http mojs io rc tween one https www npmjs com package rc tween one 2d canvas pixi js http www pixijs com fabric js https github com kangax fabric js react pixi https reactpixi org reactpixifiber https github com michalochman react pixi fiber react konva https www npmjs com package react konva isometric obelisk js https www npmjs com package obelisk js creative p5 js https www npmjs com package p5 fonts opentype js https opentype js org svg snap svg http snapsvg io rapha l http dmitrybaranovskiy github io raphael physics matter js http brm io matter js 3d webgl three js https threejs org react three https github com izzimach react three react three renderer https github com toxicfork react three renderer babylon js http www babylonjs com stackgl https github com stackgl aframe react https www npmjs com package aframe react a frame https aframe io react 360 https facebook github io react 360 physics cannon js https github com schteppe cannon js ammo js https github com kripken ammo js oimo js https github com lo th oimo js data visualization react sparklines https borisyankov github io react sparklines react trend https www npmjs com package react trend vx https vx demo now sh recharts http recharts org victory http formidable com open source victory echarts http echarts baidu com highcharts commercial https www highcharts com react highcharts https www npmjs com package react highcharts google charts https developers google com chart react google charts https www npmjs com package react google charts plotly js https plot 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npmjs com react native sound storage realm https www npmjs com package realm simple store https www npmjs com package react native simple store return to table of contents table of contents server side network http intro an overview of http https developer mozilla org en us docs web http overview introduction to http https launchschool com books http evolution of http https developer mozilla org en us docs web http basics of http evolution of http identifying resources on the web https developer mozilla org en us docs web http basics of http identifying resources on the web understanding uris http medialize github io uri js about uris html architecture of the world wide web identification https www w3 org tr webarch identification mime types https developer mozilla org en us docs web http basics of http mime types http messages https developer mozilla org en us docs web http messages connection management in http 1 x https developer mozilla org en us docs web http connection management 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grpc http www grpc io docs guides protocol buffers https developers google com protocol buffers tcp writing websocket servers https developer mozilla org en us docs web api websockets api writing websocket servers udp quic https www chromium org quic return to table of contents table of contents server side best practices saas the twelve factor app https 12factor net restful api heroku s http api design guide https geemus gitbooks io http api design content en microsoft s api design best practices https docs microsoft com en us azure architecture best practices api design rest api guidelines https github com microsoft api guidelines blob master guidelines md best practices for designing a pragmatic restful api http www vinaysahni com best practices for a pragmatic restful api principles of good restful api design https codeplanet io principles good restful api design rest api error codes 101 http blog restcase com rest api error codes 101 introducing json http json org microservices a pattern language for microservices http microservices io patterns index html microservice architecture http microservices io patterns microservices html monolithic architecture http microservices io patterns monolithic html decompose by business capability http microservices io patterns decomposition decompose by business capability html subdomain http microservices io patterns decomposition decompose by subdomain html service instance per container http microservices io patterns deployment service per container html service deployment platform http microservices io patterns deployment service deployment platform html externalized configuration http microservices io patterns externalized configuration html microservice chassis http microservices io patterns microservice chassis html service discovery server side http microservices io patterns server side discovery html client side http microservices io patterns client side discovery html service registry http microservices io patterns service registry html remote procedure invocation http microservices io patterns communication style rpi html database per service http microservices io patterns data database per service html shared database http microservices io patterns data shared database html microservices from design to deployment https www nginx com blog introduction to microservices microservices resource guide https martinfowler com microservices api gateway pattern api gateway backend for front end http microservices io patterns apigateway html why an api gateway https www nginx com blog microservices api gateways part 1 why an api gateway moving from rest to graphql https medium com frikille moving from rest to graphql e3650b6f5247 from rest to graphql https 0x2a sh from rest to graphql b4e95e94c26b graphql vs rest https dev blog apollodata com graphql vs rest 5d425123e34b serverless and graphql a perfect match for the new cloud paradigm https thenewstack io serverless graphql perfect match new cloud paradigm serverless pattern serverless deployment http microservices io patterns deployment serverless deployment html microservices without the servers https aws amazon com blogs compute microservices without the servers the next layer of abstraction in cloud computing is serverless https read acloud guru iaas paas serverless the next big deal in cloud computing 34b8198c98a2 the essential guide to serverless technologies and architectures https techbeacon com essential guide serverless technologies architectures an essential guide to the serverless ecosystem https techbeacon com essential guide serverless ecosystem serverless architecture five design patterns https thenewstack io serverless architecture five design patterns serverless code patterns https serverless com blog serverless architecture code patterns cloud distributed architecture aws well architected https aws amazon com architecture well architected azure s cloud fundamentals architecture styles https docs microsoft com en us azure architecture guide architecture styles pillars of software quality https docs microsoft com en us azure architecture guide pillars design principles https docs microsoft com en us azure architecture guide design principles index static static content hosting https docs microsoft com en us azure architecture patterns static content hosting valet key https docs microsoft com en us azure architecture patterns valet key content delivery network https docs microsoft com en us azure architecture best practices cdn queue jobs queue based load leveling https docs microsoft com en us azure architecture patterns queue based load leveling competing consumers https docs microsoft com en us azure architecture patterns competing consumers priority queue https docs microsoft com en us azure architecture patterns priority queue background jobs https docs microsoft com en us azure architecture best practices background jobs decompose federated identity https docs microsoft com en us azure 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architecture patterns scheduler agent supervisor the reactive manifesto http www reactivemanifesto org multitenant manage identity in multitenant applications https docs microsoft com en us azure architecture multitenant identity old fashioned web hosting non distributed ultimate guide to web hosting http www whoishostingthis com resources web hosting web hosting beginner guide http www webhostingsecretrevealed net web hosting beginner guide authentication authorization cookies vs tokens the definitive guide https auth0 com blog cookies vs tokens definitive guide the ins and outs of token based authentication https scotch io tutorials the ins and outs of token based authentication introduction to json web tokens https jwt io introduction an introduction to oauth 2 https www digitalocean com community tutorials an introduction to oauth 2 understanding oauth2 http www bubblecode net en 2016 01 22 understanding oauth2 the oauth bible http oauthbible com tokens used by auth0 https auth0 com docs tokens understanding refresh tokens https auth0 com learn refresh tokens how to safely store a password https codahale com how to safely store a password you wouldn t base64 a password cryptography decoded https paragonie com blog 2015 08 you wouldnt base64 a password cryptography decoded how to securely hash passwords https security stackexchange com a 31846 weak signature algorithm https developer mozilla org en us docs web security weak signature algorithm security security guide for developers https github com fallibleinc security guide for developers understanding csrf https github com pillarjs understanding csrf csrf demystified http www gnucitizen org blog csrf demystified cross site scripting xss attack https www acunetix com websitesecurity cross site scripting owasp top ten cheat sheet https www owasp org index php owasp top ten cheat sheet webappsec secure coding guidelines https wiki mozilla org webappsec secure coding guidelines node js security checklist https blog risingstack com node js security checklist tools see tooling testing testing analysis logging monitoring logging the ultimate guide https www loggly com ultimate guide category node the definitive guide for monitoring node js applications https blog risingstack com monitoring nodejs applications nodejs at scale monitoring and diagnostics https docs microsoft com en us azure architecture best practices monitoring tools see tooling workflow workflow monitoring devops deployments best practices http guides beanstalkapp com deployments best practices html start your devops journey https www atlassian com devops start your journey the practical devops playbook https www shippable com devops playbook html tools see tooling workflow workflow deployment devops return to table of contents table of contents microservices api services node js frameworks restful api middleware framework express http expressjs com koa http koajs com express middlewares logger morgan https www npmjs com package morgan express winston https www npmjs com package express winston errorhandler https www npmjs com package errorhandler response time https www npmjs com package response time http parser body parser https www npmjs com package body parser multer https www npmjs com package multer raw body https www npmjs com package raw body cookie parser https www npmjs com package cookie parser http headers and verbs cors https www npmjs com package cors method override https www npmjs com package method override performance compression https www npmjs com package compression connect timeout https www npmjs com package connect timeout security helmet https www npmjs com package helmet express validator https www npmjs com package express validator auth express jwt https www npmjs com package express jwt passport js http passportjs org proxy http proxy middleware https www npmjs com package http proxy middleware rocky https www npmjs com package rocky graphql apollo server express https www apollographql com docs apollo server servers express html express graphql https www npmjs com package express graphql rich framework configuration hapi https hapijs com realtime feathers https feathersjs com microservices micro https www npmjs com package micro seneca http senecajs org stdlib https stdlib com serverless serverless framework https github com serverless serverless ironfunctions https github com iron io functions bots botkit https www npmjs com package botkit graphql schemas and types http graphql org learn schema graphql schema language cheat sheet https wehavefaces net graphql shorthand notation cheatsheet 17cd715861b6 the fullstack tutorial for graphql https www howtographql com server apollo server https www apollographql com docs apollo server graphql tools http dev apollodata com tools graphql tools index html resolvers graphql resolvers https github com lucasconstantino graphql resolvers docgen codegen api blueprint https apiblueprint org swagger http swagger io raml http raml org parser protagonist https www npmjs com package protagonist drafter https www npmjs com package drafter renderer aglio https www npmjs com package aglio validator dredd https www npmjs com package dredd json schema http json schema org understanding json schema https spacetelescope github io understanding json schema json schema based editor https github com jdorn json editor see tooling documentation documentation scaffold boilerplate generator nodal https github com keithwhor nodal fuge http fuge io botpress https github com botpress botpress nodecube https github com dexteryy project webcube author s own project return to table of contents table of contents server side libraries node js configuration dotenv https www npmjs com package dotenv jsonfile https www npmjs com package jsonfile debugging winston https www npmjs com package winston verror https www npmjs com package verror longjohn https www npmjs com package longjohn stackman https www npmjs com package 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markdown remark http remark js org pdfkit https www npmjs com package pdfkit csv https www npmjs com package csv xml2js https www npmjs com package xml2js nlp natural https github com naturalnode natural retext https github com wooorm retext nodejieba https github com yanyiwu nodejieba return to table of contents table of contents cloud services global compute faas serverless webhook aws lambda https aws amazon com lambda google cloud functions https cloud google com functions webtask https webtask io hook io https hook io graphcool functions https www graph cool docs reference functions overview boo6uteemo amazon api gateway https aws amazon com api gateway paas see tooling workflow workflow deployment devops paas caas amazon ecs https aws amazon com ecs google container engine https cloud google com container engine storage object storage amazon s3 https aws amazon com s3 google cloud storage https cloud google com storage imgix https www imgix com dbaas in memory key value nosql 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google cloud pub sub https cloud google com pubsub kafka heroku kafka https www heroku com kafka rabbitmq compose https www compose com rabbitmq analytics amazon cloudsearch https aws amazon com cloudsearch elasticsearch amazon elasticsearch service https aws amazon com elasticsearch service elastic cloud https www elastic co cloud bonsai https bonsai io warehouse amazon redshift https aws amazon com redshift google bigquery https cloud google com bigquery baas crud realtime firebase realtime database https firebase google com products database graphql graphcool https www graph cool scaphold https scaphold io cms wordpress com rest api https developer wordpress com docs api contentful https www contentful com datocms https www datocms com graphcms https graphcms com baasic http www baasic com auth auth0 https auth0 com amazon cognito https aws amazon com cognito firebase authentication https firebase google com products auth oauth io https oauth io captcha recaptcha https www google com recaptcha search algolia https www algolia com email sendgrid https sendgrid com mailgun https www mailgun com mandrill http www mandrill com amazon ses https aws amazon com ses sms nexmo https www nexmo com twilio https www twilio com amazon sns https aws amazon com sns payment stripe https stripe com maps mapbox https www mapbox com customer support intercom https developers intercom com zendesk https developer zendesk com im discord https discordapp com developers form typeform io http docs typeform io form io https form io aiaas bdaas natural language nlp google natural language api https cloud google com natural language speech recognition speech synthesis amazon lex https aws amazon com lex google cloud speech api https cloud google com speech amazon polly https aws amazon com polly translation google cloud translation api https cloud google com translate computer vision amazon rekognition https aws amazon com rekognition google cloud vision api https cloud google com vision google cloud video intelligence api https cloud google com video intelligence return to table of contents table of contents cloud services china the evil twins inside the great firewall of china https github com dexteryy spellbook of modern webdev pull 4 compute faas serverless webhook https www aliyun com product fc scf https www qcloud com product scf api https www aliyun com product apigateway paas see tooling workflow workflow deployment devops paas caas https www aliyun com product containerservice ccs https www qcloud com product ccs daocloud https www daocloud io dcs storage object storage oss https www aliyun com product oss cos https www qcloud com product cos dbaas in memory key value nosql redis redis https www aliyun com product kvstore redis https www qcloud com product crs document nosql mongodb mongodb https www aliyun com product mongodb mongodb https www qcloud com product mongodb wide column nosql ots https www aliyun com product ots hbase hbase https cn aliyun com product hbase hbase https www qcloud com product hbase sql postgresql postgresql https www aliyun com product rds postgresql cdb for postgresql https www qcloud com product postgresql mysql mysql https www aliyun com product rds mysql cdb for mysql https www qcloud com product cdb queue mns https www aliyun com product mns cmq https www qcloud com product cmq kafka ckafka https www qcloud com product ckafka analytics opensearch https www aliyun com product opensearch tcs https www qcloud com product tcs warehouse maxcompute odps https www aliyun com product odps tbds https www qcloud com product tbds baas crud leancloud https leancloud cn docs storage overview html realtime https www wilddog com product sync overview leancloud https leancloud cn docs realtime v2 html auth https www wilddog com product auth overview captcha http www geetest com yy https www qcloud com product yy search email https www aliyun com product directmail sendcloud http sendcloud sohu com sms https www aliyun com product sms sms https www qcloud com product sms https www yunpian com https www wilddog com product message overview payment ping https www pingxx com products maps https lbs amap com getting started map http lbsyun baidu com customer support https meiqia com https www qcloud com product ics im https www wilddog com product im overview im https www qcloud com product im form https help jinshuju net articles api intro aiaas bdaas natural language nlp nlp https www qcloud com product nlp pai https help aliyun com document detail 42747 html speech recognition speech synthesis https data aliyun com product nls aai https www qcloud com product aai translation https www qcloud com product tmt computer vision ci https www qcloud com product ci https data aliyun com product ocr graphs networks clusters https data aliyun com product re cre https www qcloud com product cre https data aliyun com product graphanalytics pai https help aliyun com document detail 42750 html persona https data aliyun com product porana ir https www qcloud com product ir return to table of contents table of contents tooling testing unit testing test runner jest https facebook github io jest ava https github com avajs ava mocha https mochajs org chai http chaijs com cypress https www cypress io karma https karma runner github io web testing integration testing components enzyme http airbnb io enzyme reducers redux test utils https www npmjs com package redux test utils enzyme redux https www npmjs com package enzyme redux redux testkit https www npmjs com package redux testkit functional testing e2e testing headless browser automation devtools api headless chrome puppeteer https github com googlechrome puppeteer chromy https www npmjs com package chromy end to end tests that don t suck with puppeteer https ropig com blog end end tests dont suck puppeteer aws lambda chromeless https www npmjs com package chromeless electron prebuilt nightmare https github com segmentio nightmare webdriver api selenium webdriverjs https github com seleniumhq selenium wiki webdriverjs webdriverio http webdriver io nightwatch js http nightwatchjs org casperjs http casperjs org protractor http www protractortest org aws lambda lambdium https github com smithclay lambdium cloud browserstack automate https www browserstack com automate sauce labs https saucelabs com open source automated testing platform visual testing react storybook https storybooks js org react cosmos https github com react cosmos react cosmos browserstack https www browserstack com monkey testing gremlins js https www npmjs com package gremlins js headless browsers browsers chromium headless chrome chromium https developers google com web updates 2017 04 headless chrome chromium node js electron prebuilt https www npmjs com package electron webkit phantomjs http phantomjs org why you should stop using phantomjs https blog phantombuster com why you should stop using phantomjs f5c5f2717209 gecko slimerjs https slimerjs org in memory x11 display server xvfb https en wikipedia org wiki xvfb xvfb run http manpages ubuntu com manpages trusty man1 xvfb run 1 html headless https www npmjs com package headless docker lighthouse ci builder dockerfile headless https github com ebidel lighthouse ci blob master builder dockerfile headless l16 electron headless https hub docker com r dannysu electron headless dockerfile server side testing functional testing supertest https www npmjs com package supertest load testing k6 https k6 io loadtest https www npmjs com package loadtest benchmark testing js benchmark js https benchmarkjs com speedracer https github com ngryman speedracer stats js https github com mrdoob stats js network wrk https github com wg wrk httpstat https github com reorx httpstat test doubles https martinfowler com bliki testdouble html fakes mocks stubs https dev to milipski test doubles fakes mocks and stubs and spies fake data faker js https github com marak faker js chance js http chancejs com json schema faker https www npmjs com package json schema faker placeholder com https placeholder com http mocking nock https www npmjs com package nock monkey patching mockery https www npmjs com package mockery babel plugin rewire https www npmjs com package babel plugin rewire sinonjs http sinonjs org testdouble js https www npmjs com package testdouble best practices for spies stubs and mocks in sinon js https semaphoreci com community tutorials best practices for spies stubs and mocks in sinon js testdouble js vs sinon js http blog testdouble com posts 2016 03 13 testdouble vs sinon html analysis code coverage istanbul https istanbul js org software complexity escomplex https www npmjs com package escomplex complexity report https www npmjs com package complexity report node js security nsp https www npmjs com package nsp snyk https www npmjs com package snyk nsp advisories https nodesecurity io advisories snyk vulnerability db https snyk io vuln web page lighthouse https developers google com web tools lighthouse pwmetrics https github com paulirish pwmetrics pagespeed insights https developers google com speed pagespeed varvy seo tool https varvy com return to table of contents table of contents documentation js jsdoc3 http usejsdoc org documentation js http documentation js org jsdox http jsdox org dox https www npmjs com package dox esdoc https esdoc org react docgen https www npmjs com package react docgen api apidoc http apidocjs com graphql voyager https github com apis guru graphql voyager cli ronn http rtomayko github io ronn docopt http docopt org style guide markdown jsx docz https www docz site js storybook https storybook js org js comments react styleguidist https react styleguidist js org css comments kss knyle style sheets http warpspire com kss kss node http kss node github io kss node sc5 style guide generator http styleguide sc5 io writing static web generator gitbook https www npmjs com package gitbook readme https readme io client side rendering docute https docute js org docsify https docsify js org return to table of contents table of contents toolchain compiler transpiler preprocessor babel https babeljs io setting up es6 https leanpub com setting up es6 read babel user handbook https github com thejameskyle babel handbook blob master translations en user handbook md babel plugin handbook https github com thejameskyle babel handbook blob master translations en plugin handbook md presets preset env https babeljs io docs en next babel preset env html browserslist https github com ai browserslist preset react http babeljs io docs plugins preset react react optimize https github com thejameskyle babel react optimize plugins proposals babel progress on ecmascript proposals https github com babel proposals shims babel polyfill https github com babel babel tree master packages babel polyfill usebuiltins https babeljs io docs en next babel preset env html usebuiltins core js https github com zloirock core js async await 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com package public ip gulp http gulpjs com gulp the vision history and future of the project https medium com contrahacks gulp 3828e8126466 why you shouldn t create a gulp plugin http blog overzealous com post 74121048393 why you shouldnt create a gulp plugin or how to gulpfile api https github com gulpjs gulp blob master docs api md utilities the problem with gulp util https medium com gulpjs gulp util ca3b1f9f9ac5 through2 https www npmjs com package through2 gulp load plugins https www npmjs com package gulp load plugins gulp size https www npmjs com package gulp size gulp count https www npmjs com package gulp count gulp notify https www npmjs com package gulp notify gulp debug https www npmjs com package gulp debug gulp if https www npmjs com package gulp if gulp filter https www npmjs com package gulp filter merge stream https www npmjs com package merge stream gulp changed https www npmjs com package gulp changed gulp cached https www npmjs com package gulp cached gulp exec 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cheat sheet http k8s info cs html paas global now https zeit co now heroku heroku com heroku cli https devcenter heroku com articles heroku cli getting started china leancloud https leancloud cn docs leanengine overview html https leancloud cn docs leanengine cloudfunction guide node html https leancloud cn docs leanengine webhosting guide node html lean cli https leancloud cn docs leanengine cli html monitoring error tracking capturing client side javascript errors https www thoughtworks com radar techniques capturing client side javascript errors front end error handling https staticapps org articles front end error handling a guide to proper error handling in javascript https www sitepoint com proper error handling javascript services trackjs https trackjs com errorception https errorception com sentry https sentry io for javascript rollbar https rollbar com docs notifier rollbar js bugsnag https docs bugsnag com platforms browsers airbrake https airbrake io languages javascript 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biz guide main page terminal iterm2 https www iterm2 com iterm color schemes https github com mbadolato iterm2 color schemes hyper https hyper is awesome hyper https github com bnb awesome hyper package manager homebrew https brew sh shell oh my zsh https github com robbyrussell oh my zsh spaceship zsh theme https github com denysdovhan spaceship zsh theme zsh plugins zsh better npm completion https github com lukechilds zsh better npm completion awesome zsh plugins https github com unixorn awesome zsh plugins vim vimtutor http linuxcommand org man pages vimtutor1 html spf13 vim https github com spf13 spf13 vim yvim https github com dexteryy yvim git git it https github com jlord git it electron trygit simulator https try github io become a git guru https www atlassian com git tutorials git glossary https www atlassian com git glossary pro git index of commands https git scm com book commands commitizen https github com commitizen cz cli docker for mac https docs docker com docker for 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profont return to table of contents table of contents useful apps playground codepen http codepen io codesandbox https codesandbox io cdn for npm unpkg https unpkg com runkit https runkit com requestbin https requestbin com jsperf https jsperf com css in js playground https css in js playground com graphql playground https github com graphcool graphql playground apollo launchpad https launchpad graphql com glsl sandbox http glslsandbox com immutablejs repl http neilff github io immutable repl visual tools performance cuzillion http stevesouders com cuzillion critical path css generator https jonassebastianohlsson com criticalpathcssgenerator css cssreference io http cssreference io enjoycss http enjoycss com easing cubic bezier http cubic bezier com ceaser css easing animation tool https matthewlein com ceaser custom easing functions http www joelambert co uk morf easing functions http easings net flexbox fibonacci flexbox composer http maxsteenbergen com fibonacci css flexbox please https demo agektmr com flexbox flexy boxes http the echoplex net flexyboxes flexbox playground https demos scotch io visual guide to css3 flexbox flexbox playground demos flexplorer http bennettfeely com flexplorer animation css3 keyframes animation generator http cssanimate com mantra http jeremyckahn github io mantra bounce js http bouncejs com gradient ultimate css gradient generator http www colorzilla com gradient editor quantity queries builder http quantityqueries com shapes css triangle generator http apps eky hk css triangle generator tridiv css 3d editor http tridiv com html table generator http www tablesgenerator com html tables js keyboard event viewer https w3c github io uievents tools key event viewer html web audio playground http webaudioplayground appspot com regex101 https regex101 com debuggex https www debuggex com viewer json viewer https github com tulios json viewer xml tree https chrome google com webstore detail xml tree gbammbheopgpmaagmckhpjbfgdfkpadb js nice http www jsnice org js beautifier http jsbeautifier org graphql voyager https apis guru graphql voyager graphql docs https graphql docs com graphql visualizer graphqlviz http nathanrandal com graphql visualizer graphqlviz https github com sheerun graphqlviz ast explorer http astexplorer net devtools timeline viewer https chromedevtools github io timeline viewer text escaping and unescaping in javascript http 0xcc net jsescape html entity lookup http entity lookup leftlogic com html arrows https www toptal com designers htmlarrows docs dash https kapeli com dash devdocs http devdocs io velocity https velocity silverlakesoftware com zeal https zealdocs org automation robotjs https robotjs io return to table of contents table of contents collaboration version control workflow comparing workflows https www atlassian com git tutorials comparing workflows understanding the github flow https guides github com introduction flow a successful git branching model http nvie com posts a successful git branching model gui sourcetree https www sourcetreeapp com github github cheat sheet https github com tiimgreen github cheat sheet github help https help github com how we organize github issues a simple styleguide for tagging https robinpowered com blog best practice system for organizing and tagging github issues chrome extensions octolinker https octolinker github io octotree https github com buunguyen octotree code climate https codeclimate com browser extension awesome browser extensions for github https github com stefanbuck awesome browser extensions for github chatops what is chatops and how do i get started https www pagerduty com blog what is chatops what is chatops a guide to its evolution adoption and significance https www atlassian com blog software teams what is chatops adoption guide hubot https hubot github com adapters slack https github com slackapi hubot slack discord http npmjs com package hubot discord irc https www npmjs com package hubot irc wechat https www npmjs com package hubot weixin qq https www npmjs com package hubot qq kanban what is kanban a https leankit com learn kanban what is kanban b http kanbanblog com explained getting started with trello https trello com guide github project boards https help github com articles tracking the progress of your work with project boards presentation markdown mastering markdown https guides github com features mastering markdown markdown syntax https daringfireball net projects markdown syntax diagram mermaid https mermaidjs github io mermaid live editor https mermaidjs github io mermaid live editor slides remark https github com gnab remark remarker https github com kt3k remarker design sketch https www sketchapp com learn figma https www figma com invision https www invisionapp com atomic https atomic io proto io https proto io zeplin https zeplin io sympli https sympli io avocode https avocode com after effects http www adobe com products aftereffects html lottie https airbnb design lottie bodymovin https github com bodymovin bodymovin inspector spacetime https google github io inspectorspacetime sketch2ae https google github io sketch2ae return to table of contents table of contents | javascript nodejs universal-javascript isomorphic-javascript webapp webplatform libraries awesome learning html5 css3 | front_end |
FreeRTOS | freertos freertos 7 5 2 | os |
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Evision | div align center img width 100 height 100 src src evisionsandbox resource evision ico div div align center evision div div align center a href https www bilibili com video av46024738 a div div align center div div align center star div evision vcpkg introduction 1 br 2 yolo br 3 elas adcensus br 4 br 5 bug issues jiafeng5513 outlook com br 6 evision cmake vcpkg visual studio 2019 ide br 7 github evisionlight evision imgui qt br div align center img width 500 height 339 src doc pay png div introduction introduction 1 dependencies 1dependencies 2 directory specification 2directory specification 3 build 3build 4 deprecated version 4deprecated version 5 5 6 6 7 7 1 1 data br 2 doc br 3 package br 4 props br 5 scripts br 6 src br 7 legacy br scripts br package pthread window cmake br 2 1 visual studio 2019 c visual studio installer https visualstudio microsoft com zh hans vs br 2 cmake 3 20 download cmake https cmake org download br 3 vcpkg github for vcpkg https github com microsoft vcpkg br 4 vcpkg install eigen x64 windows br 5 vcpkg install opencv x64 windows br 6 vcpkg install boost x64 windows br 7 vcpkg install pcl x64 windows br 8 vcpkg install qt5 x64 windows br 9 mkdir sln cd sln br 10 cmake src dcmake toolchain file vcpkg root vcpkg scripts buildsystems vcpkg cmake g visual studio 16 dpointcloudviewer on br 11 visual studio evision sln br 12 cmaketargets all build br 13 evisionsandbox br 14 windows br vcpkg powershell env http proxy http 127 0 0 1 1080 3 1 cuda nvidia br 2 cuda 10 2 br 3 4 cd sln rm r br 5 cmake src dcmake toolchain file vcpkg root vcpkg scripts buildsystems vcpkg cmake g visual studio 16 dpointcloudviewer on dobjectdetection br 6 visual studio evision sln br 7 cmaketargets all build br 8 evisionsandbox br 9 windows br 4 ui 1 evisionadcensus adcensus 2 evisionelas elas 3 evisionpnp pnp 4 evisionobjdetection ui 5 evisionobjdetectionengine 6 evisionmonocularcalib 7 evisionpolytracker 8 evisioncalibrate 9 evisiondisparity 10 evisiontrace 11 evisionundistortion 12 evisioncamera 13 evisioncloudviewer 14 evisionparambridge 15 evisionutils 16 evisionsandbox ui 5 deprecated version 1 mfc https www bilibili com video av8862669 br stereovision https github com yuhuazou stereovision release br 2 cvlabmain cvlabsandbox c br vs src cvlib sln c evision br image doc cvlib sln png 1 cvlabmain wpf br 2 cvlabsandbox winfrom br 3 docking mdi br 4 mvp br 5 net 4 6 1 nuget br 6 packages br 1 aforge 2 2 5 br 2 aforge video 2 2 5 br 3 aforge video directshow 2 2 5 br 4 emgu cv 3 3 0 2824 br 5 cskin 16 1 14 3 br 6 weifenluo winformsui docking 2 1 0 br 7 zedgraph 5 1 5 br 6 1 2 1 zed realsense mynteye sdk imu ir slam br image doc cameras png 1 zed sdk uvc sdk br 2 br image doc device png br 1 usb usb usb br 7 1 https blog csdn net loser wang article details 51811347 2 darknet https github com pjreddie darknet 3 darknet windows https github com alexeyab darknet 4 stdoutredirector https github com dbzhang800 stdoutredirector 5 adcensus https wenku baidu com view 3708e0554693daef5ff73d4d html 6 adcensus 2 https www cnblogs com sinbad360 p 7842009 html 7 csdn https blog csdn net chenyusiyuan article details 8131496 8 csdn https blog csdn net poem qianmo article details 19809337 9 mei x sun x zhou m et al on building an accurate stereo matching system on graphics hardware c 2011 ieee international conference on computer vision workshops iccv workshops ieee 2011 467 474 10 geiger andreas martin roser and raquel urtasun efficient large scale stereo matching asian conference on computer vision springer berlin heidelberg 2010 11 zhang k fang y min d et al cross scale cost aggregation for stereo matching c proceedings of the ieee conference on computer vision and pattern recognition 2014 1590 1597 12 martull sarah martin peris and kazuhiro fukui realistic cg stereo image dataset with ground truth disparity maps icpr workshop trakmark2012 vol 111 no 430 2012 13 hirschmuller h stereo processing by semiglobal matching and mutual information j ieee transactions on pattern analysis and machine intelligence 2008 30 2 328 341 14 doc md 15 warpped libelas with opencv and used pangolin as gui https github com heyijia stereo elas 8 1 http blog csdn net hysteric314 article details 51357318 br | opencv stereovision qt mfc wpf emgucv | ai |
AzureLandingZone | build status https dev azure com academyazure2022 fortmu 20ltd 20 20group 203 apis build status fortmudemo branchname master https dev azure com academyazure2022 fortmu 20ltd 20 20group 203 build latest definitionid 142 branchname master introduction landing zone for fortmu ltd application development production team with this landing zone you will have a cloud based environment up and running in just a couple of clicks to build your web apps customize the platform to suit your needs through parameter files run azure pipelines yml to deploy your landing zone through pipeline run createresources py to deploy your landing zone through code editor run renamerg py to rename your resource group run resizevm py to resize a deployed virtual machine what the landing zone includes testing environment virtual network windows virtual machine postgresql database web app app service plan monitoring dashboard budget bastion connection 1 instance general purpose 2 vcores premium p2v2 virtual machine cpu start and end dates open to port https 443 version 11 windows net core 3 1 lts virtual machine memory usage customizable thresholds os disk type standardssd lrs private link connection private link connection database cpu e mail alert size standard ds1 v2 database reclaimable space patch mode automatic by os log ins monitoring diagnostics production environment virtual network windows virtual machine postgresql database web app app service plan monitoring dashboard budget bastion connection 2 instances general purpose 4 vcores premium p2v2 virtual machine cpu start and end dates open to port https 443 version 11 windows net core 3 1 lts virtual machine memory usage customizable thresholds os disk type premium lrs private link connection private link connection database cpu e mail alert size standard ds1 v2 database reclaimable space patch mode automatic by os log ins monitoring diagnostics getting started get started with your landing zone by running this bash command on your terminal to install python the libraries we will be using json and os come preinstalled install python bash sudo apt install python3 10 build your landing zone deploy landing zone through code editor 1 clone the repository to your code editor 2 run getting started installment in the terminal 3 press run or run in bash terminal bash python createresources py 4 select your environment and sign in to your azure account as prompted by the terminal deploy landing zone through devops pipeline 1 press set up build from repository 2 select your environment and sign in to your azure account when prompted by the pipeline 3 watch your environment deploy through the pipeline open your web app through the private link and you are ready to code and deploy your apps alt text readme md photo webapp png web app | cloud |
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DApp-Yield-Stacking-App | dapp yield stacking app developed a decentralized banking app where users come and deposit their tokens to the bank and in return they get rewarded with another token which we provide them in exchange which the process is called yield farming staking and unstaking rewards using ethereum smart contract with solidity and javascript with a heavy focus on test driven development using test networks like ganache and libraries like truffle mocha chai metamask and web3 js the technology used front end html5 css3 javascript react js redux backend solidity node js test networks and libraries ganache truffle mocha chai metamask web3 js ide and code editors used remix vscode package manager npm tokens used erc20 mock tether test ethers | server |
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slides-devweb | web dev slides build status https app travis ci com he arc slides devweb svg branch master https app travis ci com he arc slides devweb slides for web development course at he arc ch 3rd year bachelor emoji s afin d activer les emoji s 1 installer xelatex emoji https github com mreq xelatex emoji 2 placer les images emojione https github com ranks emojione assets la racine dans emojione assets 3 adapter xelatex emoji indice consulter travis yml | hacktoberfest | front_end |
Lean-Mobile-App-Development | lean mobile app development this is the code repository for lean mobile app development https www packtpub com application development lean mobile app development utm source github utm medium repository utm campaign 9781786467041 published by packt https www packtpub com utm source github it contains all the supporting project files necessary to work through the book from start to finish about the book lean is the ultimate methodology for creating a startup that succeeds sounds great from a theoretical point of view but what does that mean for you as an a technical co founder or mobile developer by applying the lean start up methodology to your mobile app development it will become so much easier to build apps that take google play or the app store by storm this book shows you how to bring together smarter business processes with technical know how it makes no sense to develop a brilliant app for six months or longer only to find out later that nobody is interested in it build a minimum viable product mvp first validate your hypotheses early and often discover effective product development strategies that let you put facebook s famous axiom move fast and break things into practice instructions and navigation all of the code is organized into folders each folder starts with a number followed by the application name for example chapter02 the code will look like the following func refresh sender anyobject let cngquery client querydataset wwmu gmzc cngquery orderascending title get res in switch res case dataset let data self data data data xml json or otherwise is shown as key uberclientid key string your uber client id string key ubercallbackuri key string string key lsapplicationqueriesschemes key array string uber string array in the first place this book is to inspire technical oriented cofounders of start ups and existing business technical leaders seeking to integrate lead into their development operations in addition there are some android and ios code samples that we discuss to explain some of the concepts although the concept is more important than the code you can try the sample for yourself where applicable you can find a link to the github repository containing the code for the android examples you need to have android studio 3 or above and the android sdks installed on your computer android studio is available as a free download for windows osx and other operating systems the android examples are written in kotlin and java the samples for ios requires xcode 9 or above xcode is available on osx only and you need to have a paid apple developer s account the ios examples are written in swift 4 some examples require a free registration at firebase facebook fabric or other services related products professional oracle mobile https www packtpub com virtualization and cloud professional oracle mobile utm source github utm medium repository utm campaign 9781788830959 mastering machine learning algorithms https www packtpub com big data and business intelligence mastering machine learning algorithms utm source github utm medium repository utm campaign 9781788621113 beginning reinforcement learning https www packtpub com big data and business intelligence beginning reinforcement learning utm source github utm medium repository utm campaign 9781788834247 download a free pdf i if you have already purchased a print or kindle version of this book you can get a drm free pdf version at no cost br simply click on the link to claim your free pdf i p align center a href https packt link free ebook 9781786467041 https packt link free ebook 9781786467041 a p | front_end |
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sipus-digilib | sipus https github com nikoshaa sipus digilib assets 93475727 b18890d1 152b 46ca ad33 e0eb6c301daa digital library of sman 1 blega digital library of sman 1 blega adalah sebuah platform yang dirancang khusus untuk menyediakan akses mudah dan praktis ke berbagai sumber daya pendidikan digital kepada siswa dan guru sman 1 blega badges p img alt version src https img shields io badge version 0 5 0 blue svg cacheseconds 2592000 a href https github com alizul01 polinema innovation tribe target blank img alt documentation src https img shields io badge documentation yes brightgreen svg a a href target blank img alt license mit src https img shields io badge license mit yellow svg a p contributors wildan hafidz mauludin https github com nikoshaa ahmad bima tristan ibrahim https github com voltanz iemaduddin https github com iemaduddin ibnu hajar askholani https github com askholani yuliyana rahmawati https github com ylnrahma installation 1 baca dokumentasi fork up to date https gist github com jeffcost 3843711 2 git clone https github com nikoshaa sipus digilib 3 lakukan perubahan pada file contributor txt 4 git commit m pesan commit 5 git push origin master quick start 1 menyalakan database xampp 2 composer install pada terminal 3 copy env pada latihan web lanjut 4 buat database baru dengan nama sipus digilib 5 sesuaikan nama database di file env 6 jalankan perintah php artisan migrate 7 jalankan perintah php artisan db seed 8 jalankan perintah php artisan serve license the laravel framework is open sourced software licensed under the mit license https opensource org licenses mit | laravel digilib collaborate github | server |
Visual-Transformer-Paper-Summary | awesome transformer cv if you have any problems suggestions or improvements please submit the issue or pr contents attention attention overallsurvey overallsurvey nlp nlp language language speech speech cv cv backbone classification backbone classification self supervised self supervised interpretability and robustness interpretability and robustness detection detection hoi hoi tracking tracking segmentation segmentation reid reid localization localization generation generation inpainting inpainting image enhancement image enhancement pose estimation pose estimation face face video understanding video understanding depth estimation depth estimation prediction prediction nas nas pointcloud pointcloud fashion fashion medical medical cross modal cross modal reference reference acknowledgement acknowledgement attention recurrent models of visual attention 2014 deepmind nips neural machine translation by jointly learning to align and translate iclr 2015 overallsurvey efficient transformers a survey paper https arxiv org abs 2009 06732 a survey on visual transformer paper https arxiv org abs 2012 12556 transformers in vision a survey paper https arxiv org abs 2101 01169 nlp a name language a language sequence to sequence learning with neural networks nips 2014 paper https arxiv org abs 1409 3215 code https github com bentrevett pytorch seq2seq end to end memory networks nips 2015 paper https arxiv org abs 1503 08895 code https github com nmhkahn memn2n pytorch attention is all you need nips 2017 paper https arxiv org abs 1706 03762 code b idirectional e ncoder r epresentations from t ransformers bert paper code https huggingface co transformers pretrained models https huggingface co transformers pretrained models html reformer the efficient transformer iclr2020 paper https arxiv org abs 2001 04451 code https github com lucidrains reformer pytorch linformer self attention with linear complexity aaai2020 paper https arxiv org abs 2006 04768 code https github com lucidrains linformer gpt 3 language models are few shot learners nips 2020 paper https arxiv org abs 2005 14165 code https github com openai gpt 3 a name speech a speech dual path transformer network direct context aware modeling for end to end monaural speech separation interspeech 2020 paper https arxiv org abs 2007 13975 code https github com ujscjj dptnet cv a name backbone classification a backbone classification papers and codes coat co scale conv attentional image transformers arxiv 2021 paper http arxiv org abs 2104 06399 code https github com mlpc ucsd coat sit self supervised vision transformer arxiv 2021 paper https arxiv org abs 2104 03602 code https github com sara ahmed sit vit an image is worth 16x16 words transformers for image recognition at scale vit iclr 2021 paper https arxiv org abs 2010 11929 code https github com lucidrains vit pytorch trained with extra private data do not generalized well when trained on insufficient amounts of data deit data efficient image transformers arxiv2021 paper https arxiv org abs 2012 12877 code https github com facebookresearch deit token based strategy and build upon vit and convolutional models transformer in transformer arxiv 2021 paper https arxiv org abs 2103 00112 code1 https github com lucidrains transformer in transformer code official https github com huawei noah noah research tree master tnt omninet omnidirectional representations from transformers arxiv2021 paper https arxiv org abs 2103 01075 gaussian context transformer cvpr 2021 paper https openaccess thecvf com content cvpr2021 papers ruan gaussian context transformer cvpr 2021 paper pdf general multi label image classification with transformers cvpr 2021 paper https arxiv org abs 2011 14027 code https github com qdata c tran scaling local self attention for parameter efficient visual backbones cvpr 2021 paper https arxiv org abs 2103 12731 t2t vit tokens to token vit training vision transformers from scratch on imagenet iccv 2021 paper https arxiv org abs 2101 11986 code https github com yitu opensource t2t vit swin transformer hierarchical vision transformer using shifted windows iccv 2021 paper https arxiv org abs 2103 14030 code https github com microsoft swin transformer bias loss for mobile neural networks iccv 2021 paper https arxiv org abs 2107 11170 code vision transformer with progressive sampling iccv 2021 paper https arxiv org abs 2108 01684 code https github com yuexy ps vit rethinking spatial dimensions of vision transformers iccv 2021 paper https arxiv org abs 2103 16302 code https github com naver ai pit rethinking and improving relative position encoding for vision transformer iccv 2021 paper https arxiv org abs 2107 14222 code https github com microsoft automl tree main irpe interesting repos convolutional cifar10 https github com kuangliu pytorch cifar blob master main py vision transformers cifar10 https github com kentaroy47 vision transformers cifar10 found that performance was worse than simple resnet18 the influence of hyper parameters dim of vit etc vit pytorch https github com jeonsworld vit pytorch using pretrained weights can get better results a name self supervised a self supervised emerging properties in self supervised vision transformers iccv 2021 paper https arxiv org abs 2104 14294 code https github com facebookresearch dino an empirical study of training self supervised vision transformers iccv 2021 paper https arxiv org abs 2104 02057 code https github com searobbersduck moco v3 pytorch a name interpretability and robustness a interpretability and robustness transformer interpretability beyond attention visualization cvpr 2021 paper https arxiv org abs 2012 09838 code https github com hila chefer transformer explainability on the adversarial robustness of visual transformers arxiv 2021 paper https arxiv org abs 2103 15670 robustness verification for transformers iclr 2020 paper https arxiv org abs 2002 06622 code https github com shizhouxing robustness verification for transformers pretrained transformers improve out of distribution robustness acl 2020 paper https arxiv org abs 2004 06100 code https github com camelop nlp robustness a name detection a detection detr end to end object detection with transformers eccv2020 paper https arxiv org abs 2005 12872 code https github com facebookresearch detr deformable detr deformable transformers for end to end object detection iclr2021 paper https openreview net forum id gz9hcdwe6ke code https github com fundamentalvision deformable detr end to end object detection with adaptive clustering transformer arxiv2020 paper https arxiv org abs 2011 09315 up detr unsupervised pre training for object detection with transformers arxiv2020 paper https arxiv org abs 2011 09094 rethinking transformer based set prediction for object detection arxiv2020 paper https arxiv org pdf 2011 10881 pdf zhihu https zhuanlan zhihu com p 326647798 end to end lane shape prediction with transformers wacv 2021 paper https arxiv org pdf 2011 04233 pdf code https github com liuruijin17 lstr vit frcnn toward transformer based object detection arxiv2020 paper https arxiv org abs 2012 09958 line segment detection using transformers cvpr 2021 paper https arxiv org abs 2101 01909 code https github com mlpc ucsd letr facial action unit detection with transformers cvpr 2021 paper https openaccess thecvf com content cvpr2021 papers jacob facial action unit detection with transformers cvpr 2021 paper pdf code adaptive image transformer for one shot object detection cvpr 2021 paper https openaccess thecvf com content cvpr2021 papers chen adaptive image transformer for one shot object detection cvpr 2021 paper pdf code self attention based text knowledge mining for text detection cvpr 2021 paper https openaccess thecvf com content cvpr2021 papers wan self attention based text knowledge mining for text detection cvpr 2021 paper pdf code https github com cvi szu stkm pyramid vision transformer a versatile backbone for dense prediction without convolutions iccv 2021 paper https arxiv org abs 2102 12122 code https github com whai362 pvt group free 3d object detection via transformers iccv 2021 paper https arxiv org abs 2104 00678 code https github com zeliu98 group free 3d fast convergence of detr with spatially modulated co attention iccv 2021 paper https arxiv org abs 2101 07448 code https github com abc403 smca replication a name hoi a hoi end to end human object interaction detection with hoi transformer cvpr 2021 paper https arxiv org abs 2103 04503 code https github com bbepoch hoitransformer hotr end to end human object interaction detection with transformers cvpr 2021 paper https arxiv org abs 2104 13682 code https github com kakaobrain hotr a name tracking a tracking transformer meets tracker exploiting temporal context for robust visual tracking cvpr 2021 paper https arxiv org abs 2103 11681 code https github com 594422814 transformertrack transtrack multiple object tracking with transformer cvpr 2021 paper https arxiv org abs 2012 15460 code https github com peizesun transtrack transformer tracking cvpr 2021 paper https arxiv org abs 2103 15436 code https github com chenxin dlut transt learning spatio temporal transformer for visual tracking iccv 2021 paper https arxiv org abs 2103 17154 code https github com researchmm stark a name segmentation a segmentation setr rethinking semantic segmentation from a sequence to sequence perspective with transformers cvpr 2021 paper https arxiv org abs 2012 15840 code https github com fudan zvg setr trans2seg transparent object segmentation with transformer arxiv2021 paper https arxiv org abs 2101 08461 code https github com xieenze trans2seg end to end video instance segmentation with transformers arxiv2020 paper https arxiv org abs 2011 14503 zhihu https zhuanlan zhihu com p 343286325 max deeplab end to end panoptic segmentation with mask transformers cvpr 2021 paper https arxiv org pdf 2012 00759 pdf official code https github com google research deeplab2 blob main g3doc projects max deeplab md unofficial code https github com conradry max deeplab medical transformer gated axial attention for medical image segmentation arxiv 2020 paper https arxiv org pdf 2102 10662 pdf code https github com jeya maria jose medical transformer sstvos sparse spatiotemporal transformers for video object segmentation cvpr 2021 paper https arxiv org abs 2101 08833 code https github com dukebw sstvos a name reid a reid diverse part discovery occluded person re identification with part aware transformer cvpr 2021 paper https arxiv org abs 2106 04095 code a name localization a localization loftr detector free local feature matching with transformers cvpr 2021 paper https arxiv org abs 2104 00680 code https github com zju3dv loftr mist multiple instance spatial transformer cvpr 2021 paper https arxiv org pdf 1811 10725 code https github com ubc vision mist a name generation a generation variational transformer networks for layout generation cvpr 2021 paper https arxiv org abs 2104 02416 code https github com zlinao variational transformer transgan two transformers can make one strong gan paper https arxiv org pdf 2102 07074 pdf code https github com vita group transgan taming transformers for high resolution image synthesis cvpr 2021 paper https arxiv org abs 2012 09841 code https github com compvis taming transformers igpt generative pretraining from pixels icml 2020 paper https cdn openai com papers generative pretraining from pixels v2 pdf code https github com openai image gpt generative adversarial transformers arxiv 2021 paper https arxiv org abs 2103 01209 code https github com dorarad gansformer layouttransformer scene layout generation with conceptual and spatial diversity cvpr2021 paper https openaccess thecvf com content cvpr2021 html yang layouttransformer scene layout generation with conceptual and spatial diversity cvpr 2021 paper html code https github com davidhalladay layouttransformer spatial temporal transformer for dynamic scene graph generation iccv 2021 paper https arxiv org abs 2107 12309 a name inpainting a inpainting sttn learning joint spatial temporal transformations for video inpainting eccv 2020 paper https arxiv org abs 2007 10247 code https github com researchmm sttn a name image enhancement a image enhancement pre trained image processing transformer cvpr 2021 paper https arxiv org abs 2012 00364 ttsr learning texture transformer network for image super resolution cvpr2020 paper https arxiv org abs 2006 04139 code https github com researchmm ttsr a name pose estimation a pose estimation pose recognition with cascade transformers cvpr 2021 paper https arxiv org abs 2104 06976 code https github com mlpc ucsd prtr transpose towards explainable human pose estimation by transformer arxiv 2020 paper https arxiv org abs 2012 14214 code https github com yangsenius transpose hand transformer non autoregressive structured modeling for 3d hand pose estimation eccv 2020 paper https www ecva net papers eccv 2020 papers eccv papers 123700018 pdf hot net non autoregressive transformer for 3d hand object pose estimation acmmm 2020 paper https cse buffalo edu jmeng2 publications hotnet mm20 end to end human pose and mesh reconstruction with transformers cvpr 2021 paper https arxiv org abs 2012 09760 code https github com microsoft meshtransformer 3d human pose estimation with spatial and temporal transformers arxiv 2020 paper https arxiv org pdf 2103 10455 pdf code https github com zczcwh poseformer end to end trainable multi instance pose estimation with transformers arxiv 2020 paper https arxiv org abs 2103 12115 a name face a face robust facial expression recognition with convolutional visual transformers arxiv 2020 paper https arxiv org abs 2103 16854 clusformer a transformer based clustering approach to unsupervised large scale face and visual landmark recognition cvpr 2021 paper https openaccess thecvf com content cvpr2021 html nguyen clusformer a transformer based clustering approach to unsupervised large scale face cvpr 2021 paper html code https github com lucidrains timesformer pytorch a name video understanding a video understanding is space time attention all you need for video understanding arxiv 2020 paper https arxiv org abs 2102 05095 code https github com lucidrains timesformer pytorch temporal relational crosstransformers for few shot action recognition cvpr 2021 paper https arxiv org abs 2101 06184 code https github com tobyperrett trx self supervised video hashing via bidirectional transformers cvpr 2021 paper https openaccess thecvf com content cvpr2021 html li self supervised video hashing via bidirectional transformers cvpr 2021 paper html ssan separable self attention network for video representation learning cvpr 2021 paper https arxiv org abs 2105 13033 a name depth estimation a depth estimation adabins depth estimation using adaptive bins cvpr 2021 paper https openaccess thecvf com content cvpr2021 papers bhat adabins depth estimation using adaptive bins cvpr 2021 paper pdf code https github com shariqfarooq123 a name prediction a prediction multimodal motion prediction with stacked transformers cvpr 2021 paper https arxiv org pdf 2103 11624 pdf code https github com decisionforce mmtransformer deep transformer models for time series forecasting the influenza prevalence case paper https arxiv org pdf 2001 08317 pdf transformer networks for trajectory forecasting icpr 2020 paper https arxiv org abs 2003 08111 code https github com fgiuliari trajectory transformer spatial channel transformer network for trajectory prediction on the traffic scenes arxiv 2021 paper https arxiv org abs 2101 11472 code pedestrian trajectory prediction using context augmented transformer networks icra 2020 paper https arxiv org abs 2012 01757 code spatio temporal graph transformer networks for pedestrian trajectory prediction eccv 2020 paper https www ecva net papers eccv 2020 papers eccv papers 123570494 pdf code https github com majiker star hierarchical multi scale gaussian transformer for stock movement prediction paper https www ijcai org proceedings 2020 0640 pdf single shot motion completion with transformer arxiv2021 paper https arxiv org abs 2103 00776 code https github com fuxicv ssmct a name nas a nas hr nas searching efficient high resolution neural architectures with transformers cvpr 2021 paper https arxiv org abs 2106 06560 code https github com dingmyu hr nas autoformer searching transformers for visual recognition iccv 2021 paper https arxiv org abs 2107 00651 code https github com microsoft automl a name pointcloud a pointcloud multi modal fusion transformer for end to end autonomous driving cvpr 2021 paper https arxiv org abs 2104 09224 code https github com autonomousvision transfuser point 4d transformer networks for spatio temporal modeling in point cloud videos cvpr 2021 paper https openaccess thecvf com content cvpr2021 html fan point 4d transformer networks for spatio temporal modeling in point cloud cvpr 2021 paper html a name fashion a fashion kaleido bert vision language pre training on fashion domain cvpr 2021 paper https arxiv org abs 2103 16110 code https github com mczhuge kaleido bert a name medical a medical lesion aware transformers for diabetic retinopathy grading cvpr 2021 paper https openaccess thecvf com content cvpr2021 html sun lesion aware transformers for diabetic retinopathy grading cvpr 2021 paper html a name cross modal a cross modal thinking fast and slow efficient text to visual retrieval with transformers cvpr 2021 paper https arxiv org abs 2103 16553 revamping cross modal recipe retrieval with hierarchical transformers and self supervised learning cvpr2021 paper https www amazon science publications revamping cross modal recipe retrieval with hierarchical transformers and self supervised learning code https github com amzn image to recipe transformers topological planning with transformers for vision and language navigation cvpr 2021 paper https arxiv org abs 2012 05292 multi stage aggregated transformer network for temporal language localization in videos cvprr 2021 paper https openaccess thecvf com content cvpr2021 html zhang multi stage aggregated transformer network for temporal language localization in videos cvpr 2021 paper html vln bert a recurrent vision and language bert for navigation cvpr 2021 paper https arxiv org abs 2011 13922 code https github com yiconghong recurrent vln bert less is more clipbert for video and language learning via sparse sampling cvpr 2021 paper https arxiv org abs 2102 06183 code https github com jayleicn clipbert reference attention 1 2 zhihu1 https zhuanlan zhihu com p 47063917 zhihu2 https zhuanlan zhihu com p 47282410 self attention mechanism https www cnblogs com robert dlut p 8638283 html transformer zhihu https zhuanlan zhihu com p 44121378 csdn https blog csdn net longxinchen ml article details 86533005 rnn seq2seq attention https zhuanlan zhihu com p 51383402 seq2seq and transformer implementation https github com bentrevett pytorch seq2seq end to end memory networks zhihu https zhuanlan zhihu com p 29679742 illustrating the key query value in attention https medium com b terryjack deep learning the transformer 9ae5e9c5a190 transformer in cv https towardsdatascience com transformer in cv bbdb58bf335e cvpr2021 papers with code https github com amusi cvpr2021 papers with code iccv2021 papers with code https github com amusi iccv2021 papers with code acknowledgement thanks for the awesome survey papers of transformer | transformer computer-vision papers awesome attention detr segmentation vit attention-visualization survey transformer-networks visual-transformer | ai |
HoloLens2ForCV | page type sample name hololens2forcv samples description hololens 2 research mode samples showcasing raw streams on device including depth camera gray scale cameras and imu languages cpp products windows mixed reality hololens hololens2forcv samples hololens 2 research mode enables access to the raw streams on device depth camera gray scale cameras imu by releasing the research mode api together with a set of tools and sample apps we want to make it easier to use hololens 2 as a powerful computer vision and robotics research device the project was launched at eccv 2020 we plan to extend it over time and welcome contributions from the research community contents this repository contains documentation and samples for hololens 2 research mode take a look at the api documentation https github com microsoft hololens2forcv blob main docs researchmode apidoc pdf to get familiar with the new hololens 2 research mode api take a look at the slides of the eccv tutorial https github com microsoft hololens2forcv tree main docs eccv2020 tutorial to obtain detailed information about research mode and its main features read about how to set up your device and learn how to use the apps in this repository take a look at this technical report https arxiv org pdf 2008 11239 pdf for an introduction to research mode the repository contains four sample apps the calibrationvisualization app https github com microsoft hololens2forcv tree main samples calibrationvisualization shows a visualization of depth and gray scale cameras coordinate frames live on device the camerawithcvandcalibration app https github com microsoft hololens2forcv tree main samples camerawithcvandcalibration shows how to process research mode streams live on device it uses opencv to detect aruco markers in the two frontal gray scale cameras and triangulate the detections the sensorvisualization app https github com microsoft hololens2forcv tree main samples sensorvisualization shows how to visualize research mode streams live on device the streamrecorder app https github com microsoft hololens2forcv tree main samples streamrecorder shows how to capture simultaneously research mode streams depth and gray scale cameras plus head hand and eye tracking save the streams to disk on device it also contains a set of python scripts for offline postprocessing the streamrecorder app uses cannon https github com microsoft hololens2forcv tree main samples streamrecorder streamrecorderapp cannon a collection of wrappers and utility code for building native mixed reality apps using c direct3d and windows perception apis it can be used as is outside research mode for fast and easy native development setup the earliest build that fully supports research mode is 19041 1364 please join the windows insider program to get preview builds after that in the device portal enable research mode different than recording mode see https github com microsoft hololens2forcv blob main docs eccv2020 tutorial eccv2020 researchmode api pdf slides 6 7 and 8 or setup section in https github com microsoft hololens2forcv blob main docs researchmode apidoc pdf finally only arm64 applications are supported for now citing our work if you find hololens 2 research mode useful for your research please cite our work article hl2 rm title hololens 2 research mode as a tool for computer vision research author dorin ungureanu and federica bogo and silvano galliani and pooja sama and xin duan and casey meekhof and jan st u hmer and thomas j cashman and bugra tekin and johannes l sch o nberger and bugra tekin and pawel olszta and marc pollefeys journal arxiv 2008 11239 year 2020 contributing this project welcomes contributions and suggestions most contributions require you to agree to a contributor license agreement cla declaring that you have the right to and actually do grant us the rights to use your contribution for details visit https cla opensource microsoft com when you submit a pull request a cla bot will automatically determine whether you need to provide a cla and decorate the pr appropriately e g status check comment simply follow the instructions provided by the bot you will only need to do this once across all repos using our cla this project has adopted the microsoft open source code of conduct https opensource microsoft com codeofconduct for more information see the code of conduct faq https opensource microsoft com codeofconduct faq or contact opencode microsoft com mailto opencode microsoft com with any additional questions or comments | ai |
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Employee_Database_SQL | employee database sql create table relationships with primary and foreign keys explain entity relationships erd diagrams create a database create tables import csv files into sql performed sql queries including joins aggregate functions and ordering erd erdiagram png | server |
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info | cs510 course information course syllabus syllabus cs510 2017f pdf welcome to the cs510 course information readme file refer to this information throughout the semester for helpful tutorials references and tips please read the getting started gettingstarted md guide for orientation including how to create accounts on slack github and cocalc and manage the homework classwork work flow getting started click here first gettingstarted md primary course links try here first cocalc https cocalc org br collaborative calculation in the cloud free ubuntu linux servers that we will use for the course slack scststudents https scststudents slack com channel cs510 2017f br professional communication tool industry standard chat application that we will use for the course python scipy tutorials http www scipy lectures org br official scipy tutorials primary python resource we will use for the course course reference slides try here next check back throughout the semester for updates to these slides as they are live documents that are continually being improved 1 linux bash overview http slides com profdressel linux bash overview 1 vim overview http slides com profdressel vim overview 1 git overview http slides com profdressel git overview 1 ipython jupyter overview http slides com profdressel jupyter overview 1 numpy pandas overview http slides com profdressel numpy and pandas overview 1 python classes objects overview http slides com profdressel python objects overview 1 julia overview http slides com profdressel julia overview other resources read as needed coding standards chapman coding standards chapman 20coding 20standards pdf br chapman university cpsc coding standards use for your code python style guide official google https google github io styleguide pyguide html br official google style guide for python use for your code c style guide official google https en wikibooks org wiki c programming structure and style br common wisdom for c programming style use for your code c style guide official google https google github io styleguide cppguide html br official google style guide for c use for your code github resources github hello world https guides github com activities hello world br tutorial of a simple example that demonstrates the github workflow github flow guide https guides github com introduction flow br understand the flow of how github works for source code management mastering markdown https guides github com features mastering markdown br learn concise syntax for writing beautifully formatted html easily in readme files and jupyter notebooks git resources the git parable http tom preston werner com 2009 05 19 the git parable html br understand the logic behind why git is the way it is trygit tutorial https try github io levels 1 challenges 1 br interactive tutorial for using git git tutorial http git scm com docs gittutorial br official git tutorial git user manual http git scm com docs user manual html br official git manual latex resources latex tutorial https www latex tutorial com br friendly tutorial of how latex works and how to use it overleaf com https www overleaf com br alternative online collaborative latex editor with many convenient templates learn latex in y minutes https learnxinyminutes com docs latex br quick overview of the essential syntax latex wikibook https en wikibooks org wiki latex br more comprehensive reference textbook linux bash resources introductory linux bash tutorial http linuxcommand org lc3 learning the shell php br user friendly introductory tutorial of how to use the linux command line linux bash tutorial http ryanstutorials net linuxtutorial br alternative introductory tutorial bash guide for beginners http tldp org ldp bash beginners guide html br introductory scripting with bash shell scripting tutorial http www shellscript sh br intermediate scripting with bash vim resources tip copy the vimrc config file from this repository to your linux home directory interactive vim tutorial http openvim com br friendly step by step tutorial of how to use vim productively to edit code vim cheat sheet http vim rtorr com br concise summary of key commands vim reference card http tnerual eriogerg free fr vimqrc pdf br alternative concise summary of key commands vim for python http www fullstackpython com vim html br recommended vim configuration for editing python code python resources python scipy tutorials http www scipy lectures org br official scipy tutorial learning python scipy https lectures quantecon org py learning python html br excellent short introduction to scientific python interactive python tutorial http www learnpython org br interactive tutorial for basic python as a refresher learn python in y minutes https learnxinyminutes com docs python br concise summary of basic syntax official python tutorial https docs python org tutorial br official basic python tutorial julia resources learning julia https lectures quantecon org jl learning julia html br excellent short introduction to julia for scientific programming introduction to julia http ucidatascienceinitiative github io introtojulia br uc irvine introduction to julia julia documentation http julia readthedocs io en latest manual introduction br official julia documentation learn julia in y minutes https learnxinyminutes com docs julia br concise summary of basic syntax matlab python julia r comparison http sebastianraschka com articles 2014 matrix cheatsheet html br comparison of the most common data science programming languages c resources essentials of c https www raspberrypi org magpi learn code c br excellent short textbook introducing c originally for raspberry pi devices learn c in y minutes https learnxinyminutes com docs c br concise summary of essential syntax c cheat sheet https www cheatography com ashlyn black cheat sheets c reference br even more concise cheat sheet c programming wikibook https en wikibooks org wiki c programming br community sourced textbook for c programming make resources learn make in y minutes https learnxinyminutes com docs make br concise summary of the essentials of make c resources c tutorial http www cplusplus com doc tutorial br official tutorial for learning c quickly c essentials https tfetimes com wp content uploads 2015 09 cppessentials pdf br excellent in depth book for learning c systematically free perks github developer pack https education github com pack br free stuff just for being a student peruse at your leisure | server |
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serverless-nlp | serverless nlp demo of a serverless natural language processing service this app uses spacy https https github com explosion spacy deep learning nlp natural language processing library chalice https github com aws chalice serverless python framework aws lambda https aws amazon com lambda faas compute service api gateway https aws amazon com api gateway api management service dashbird io https dashbird io monitoring logging and anomaly detection quick demo we ve deployed a demo api for this application using aws lambda https aws amazon com lambda and api gateway https aws amazon com api gateway you can try examples with a pre determined text on these urls sentence extraction https g5kl1e9fhf execute api us east 1 amazonaws com api example sentence https g5kl1e9fhf execute api us east 1 amazonaws com api example sentence named entity recognition https g5kl1e9fhf execute api us east 1 amazonaws com api example named entity https g5kl1e9fhf execute api us east 1 amazonaws com api example named entity part of speech tagging https g5kl1e9fhf execute api us east 1 amazonaws com api example part of speech https g5kl1e9fhf execute api us east 1 amazonaws com api example part of speech the text used for the examples above is lambda is an event driven serverless computing platform provided by amazon as a part of the amazon web services it is a computing service that runs code in response to events and automatically manages the computing resources required by that code it was introduced in november 2014 andy jassy is the ceo of amazon web services the company earned 17 4 billion in revenue and 4 331 billion in profits in the year of 2017 source wikipedia org to try the api with your own text sample use curl curl xpost h content type application json d data type named entity text your text goes here model name en core web sm https g5kl1e9fhf execute api us east 1 amazonaws com api extract in the data type argument you can provide sentence named entity part of speech this demo api only supports text in english having only one model deployed en core web sm you can clone fork this repo and deploy other spacy models https spacy io usage models to support multiple languages pre requisites python 3 6 https www python org downloads release python 370 pip 18 1 https pypi org project pip | ai |
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MachineLearningTrick | machine learning trick gbdt feature blending stacking cascadeforest 1 xgboost md 2 md gbdt xgboost 3 xgboost feature py xgboost 4 xgboost md xgboost 4 blending py http blog csdn net a358463121 article details 53054686 https github com emanuele kaggle pbr blob master blend py 5 stacking py https github com mlwave kaggle ensemble guide | ai |
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Cloud-Edge-Deployment-Trade-off-in-Anomalous-Sound-Detection-Application | cloud edge deployment trade off in anomalous sound detection asd application python code written for jeff christoffels master thesis cloud edge deployment trade off in anomalous sound detection asd application submitted to obtain the master of engineering computer science degree baseline models from yohei kawaguchi keisuke imoto yuma koizumi noboru harada daisuke niizumi kota dohi ryo tanabe harsh purohit and takashi endo description and discussion on dcase 2021 challenge task 2 unsupervised anomalous sound detection for machine condition monitoring under domain shifted conditions in arxiv e prints 2106 04492 2021 url https arxiv org abs 2106 04492 noboru harada daisuke niizumi daiki takeuchi yasunori ohishi masahiro yasuda shoichiro saito toyadmos2 another dataset of miniature machine operating sounds for anomalous sound detection under domain shift conditions in arxiv e prints 2106 02369 2021 url https arxiv org abs 2106 02369 ryo tanabe harsh purohit kota dohi takashi endo yuki nikaido toshiki nakamura and yohei kawaguchi mimii due sound dataset for malfunctioning industrial machine investigation and inspection with domain shifts due to changes in operational and environmental conditions in arxiv e prints 2105 02702 2021 url https arxiv org abs 2105 02702 the code to train and evaluate the autoencoder based baseline can be found here https github com y kawagu dcase2021 task2 baseline ae the code to train and evaluate the mobilenetv2 based baseline can be found here https github com y kawagu dcase2021 task2 baseline mobile net v2 | cloud |
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PyVision | pyvision ready to use implementations of some of the most common computer vision algorithms in pytorch only currently available architectures multi task cascaded convolutional neural network mtcnn a sota face and facial landmark detection architecture check out this https github com pranjaldatta pyvision tree master pyvision misc mtcnn out for more details yolov3 the sota object detection algorithm for more details read the docs https github com pranjaldatta pyvision tree master pyvision detection yolov3 facenet a unified embedding for face recognition and clustering one of the most popular architectures used for facial recognition for more details check here https github com pranjaldatta pyvision tree master pyvision face detection facenet detection transformer detr an end to end object detection architecture using transformers for more details check here https github com pranjaldatta pyvision tree master pyvision detection detr neural style transfer nst transfer style from one image into another for more details check here https github com pranjaldatta pyvision tree master pyvision misc neuralstyletransfer pyramid scene parsing network pspnet instance segmentation architecture that makes use of pyramid pooling module for better results for more details check here https github com pranjaldatta pyvision tree master pyvision segmentation pspnet for full list of architectures that has been ported or are in the process of being ported check here https github com pranjaldatta pyvision blob master docs developing md installation 1 run the code in your terminal to clone the master branch which contains the working code git clone https github com pranjaldatta pyvision git single branch branch master 2 then go to the repository root by pasting the command given below into your terminal cd pyvision 3 run the following command in the terminal to install pyvision into the current virtual or conda environment pip install 4 you are good to go contributing for contribution guidelines please look here https github com pranjaldatta pyvision tree master docs contributing md contributions are always welcome todo populate with more architectures obviously x come up with an efficient way to make the repository minimal i e assets like weights will only be downloaded on as you need basis all weights are hosted on srm mic google drive and downloaded using gdown x come up with an efficient way to ensure that heavy architecture specific dependecies are installed only when required all heavy assets are installed only when model is being used note currently its working only in pre configured conda environment with all dependencies installed p s star the repo if you liked the work | ai |
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2020-ces-iac-capi | cloud engineering summit infrastructure as code and cluster api this repository contains slides example code and manifests for use in or with the 2020 cloud engineering summit session titled exploring the intersection of infrastructure as code and cluster api | cloud |
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Flutter-MVVM | flutter mvvm example of mobile application development with flutter sdk using model view viewmodel architecture to build reactive scalable and maintainble applications | flutter | front_end |
ml_implementation | implementation of machine learning introduction these are the implementation of machine learning algorithms from scratch x linear regression linear regression x least square method linear regression least square method py x logistic regression logistic regression x logistic regression logistic regression logistic regression py x distributed logistic regression logistic regression distributed logistic regression py x bayes bayes x navie bayes bayes navie bayes py x decision tree decision tree x c4 5 decision tree c45 decision tree decision tree py x id3 decision tree id3 decision tree decision tree py random forest gradient boosting tree x neural network neural network x perception neural network perception py x neural network neural network neural network py x svm svm x svm svm svm py fm fm random forest random forest kmeans kmeans condictional random field condictional random field condictional random field condictional random field condictional random field py others others sigmoid others sigmoid standard deviation others standard deviation normal distribution others normal distribution auto gradient others autogradient x random walk others random walk | machine-learning python implementation | ai |
nlp | natural language processing nlp usage example for your code import nlp from https deno land x nlp 1 2 1 nlp ts import exampletrainingdata from https deno land x nlp 1 2 1 training data ts const languages en const trainingresult await nlp train exampletrainingdata documents exampletrainingdata answers languages console log trainingresult n json stringify trainingresult const response await nlp getresponse hi languages 0 trainingresult clientid console log response n json stringify response call usage example via command line deno run allow net reload https deno land x nlp 1 2 1 usage example ts execute the tests deno test allow net reload https deno land x nlp test ts background info this module leverages https github com fancy flashcard fancy nlp until a pure deno based solution is available the following comment might be interesting if you want to look into some background info https github com axa group nlp js issues 510 issuecomment 664246574 feel free to contribute via pull requests link to deno this module can be found here https deno land x nlp https deno land x nlp support my open source contributions if you like my work please consider downloading the brave browser via my promotion link https brave com fan464 https brave com fan464 https brave com https brave com wp content uploads 2019 01 logotype full color svg | natural-language-processing natural-language-understanding natural-language-generation communication | ai |
Python-Machine-Learning-Second-Edition | python machine learning second edition this is the code repository for python machine learning second edition https www packtpub com big data and business intelligence python machine learning second edition utm source github utm medium repository utm campaign 9781787125933 published by packt https www packtpub com utm source github it contains all the supporting project files necessary to work through the book from start to finish about the book this highly acclaimed book has been extended and modernized to now include the popular tensorflow deep learning library the scikit learn code has also been fully updated to include recent improvements and additions to this versatile machine learning library the result is a new edition of this classic book at the cutting edge of machine learning instructions and navigation all of the code is organized into folders each folder starts with a number followed by the application name for example chapter02 the code will look like the following from sklearn neighbors import kneighborsclassifier knn kneighborsclassifier n neighbors 5 p 2 metric minkowski knn fit x train std y train plot decision regions x combined std y combined classifier knn test idx range 105 150 plt xlabel petal length standardized plt ylabel petal width standardized plt show the execution of the code examples provided in this book requires an installation of python 3 6 0 or newer on macos linux or microsoft windows we will make frequent use of python s essential libraries for scientific computing throughout this book including scipy numpy scikit learn matplotlib and pandas the first chapter will provide you with instructions and useful tips to set up your python environment and these core libraries we will add additional libraries to our repertoire moreover installation instructions are provided in the respective chapters the nltk library for natural language processing chapter 8 applying machine learning to sentiment analysis the flask web framework chapter 9 embedding a machine learning algorithm into a web application the seaborn library for statistical data visualization chapter 10 predicting continuous target variables with regression analysis and tensorflow for efficient neural network training on graphical processing units chapters 13 to 16 you can also find the code files at the following link https github com rasbt python machine learning book 2nd edition related products python machine learning https www packtpub com big data and business intelligence python machine learning utm source github utm medium repository utm campaign 9781783555130 python end to end data analysis https www packtpub com big data and business intelligence python end end data analysis utm source github utm medium repository utm campaign 9781788394697 python real world machine learning https www packtpub com big data and business intelligence python real world machine learning utm source github utm medium repository utm campaign 9781787123212 download a free pdf i if you have already purchased a print or kindle version of this book you can get a drm free pdf version at no cost br simply click on the link to claim your free pdf i p align center a href https packt link free ebook 9781787125933 https packt link free ebook 9781787125933 a p | ai |
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cheatsheets-ai | ai cheatsheets essential cheat sheets for deep learning and machine learning engineers website https aicheatsheets com p align center img width 50 height auto src triplebyte logo png p p align center looking for a new job take triplebyte s a href https triplebyte com a zyavvec d quiz a and get a job at top companies like adobe dropbox and instacart p website 1 https github com kailashahirwar cheatsheets ai blob master screenshots website png website 2 https github com kailashahirwar cheatsheets ai blob master screenshots website 2 png tensorflow 1 https github com kailashahirwar cheatsheets ai blob master screenshots tensorflow1 png medium article https medium com kailashahirwar essential cheat sheets for machine learning and deep learning researchers efb6a8ebd2e5 medium article https github com kailashahirwar cheatsheets ai blob master screenshots medium article png reddit thread https www reddit com r python comments cyslju ai cheatsheets now learn tensorflow keras pytorch utm source share utm medium web2x reddit post https github com kailashahirwar cheatsheets ai blob master screenshots reddit post png tensorflow https github com kailashahirwar cheatsheets ai blob master pdfs tensorflow pdf br keras https github com kailashahirwar cheatsheets ai blob master keras jpg br neural networks zoo https github com kailashahirwar cheatsheets ai blob master neural 20networks 20zoo png br numpy https github com kailashahirwar cheatsheets ai blob master numpy png br scipy https github com kailashahirwar cheatsheets ai blob master scipy png br pandas 1 https github com kailashahirwar cheatsheets ai blob master pandas 1 jpg br pandas 2 https github com kailashahirwar cheatsheets ai blob master pandas 2 jpg br pandas 3 https github com kailashahirwar cheatsheets ai blob master pandas 3 png br scikit learn https github com kailashahirwar cheatsheets ai blob master scikit 20learn png br matplotlib https github com kailashahirwar cheatsheets ai blob master matplotlib png br seaborn https github com kailashahirwar cheatsheets ai blob master seaborn png br ggplot2 1 https github com kailashahirwar cheatsheets ai blob master ggplot2 1 jpg br ggplot2 2 https github com kailashahirwar cheatsheets ai blob master ggplot2 2 jpg br pyspark https github com kailashahirwar cheatsheets ai blob master pyspark jpg br pyspark rdd https github com kailashahirwar cheatsheets ai blob master pyspark rdd png br pyspark sql https github com kailashahirwar cheatsheets ai blob master pyspark sql png br r studio dplyr tidyr 1 https github com kailashahirwar cheatsheets ai blob master data 20wrangling 20with 20dplyr 20and 20tidyr 20 20r 20studio 1 jpg br r studio dplyr tidyr 2 https github com kailashahirwar cheatsheets ai blob master data 20wrangling 20with 20dplyr 20and 20tidyr 20 20r 20studio 2 jpg br neural network cells https github com kailashahirwar cheatsheets ai blob master neural 20network 20cells png br neural network graphs https github com kailashahirwar cheatsheets ai blob master neural 20network 20graphs png br deep learning cheat sheet https github com kailashahirwar cheatsheets ai blob master deep 20learning 20cheat 20sheet hacker 20noon pdf br dask1 https github com kailashahirwar cheatsheets ai blob master dask1 png dask2 https github com kailashahirwar cheatsheets ai blob master dask2 png dask3 https github com kailashahirwar cheatsheets ai blob master dask3 png dask4 https github com kailashahirwar cheatsheets ai blob master dask4 png all cheat sheets pdf https github com kailashahirwar cheatsheets ai blob master all 20cheat 20sheets pdf br medium article https medium com kailashahirwar essential cheat sheets for machine learning and deep learning researchers efb6a8ebd2e5 license mit license https github com kailashahirwar cheatsheets ai blob master license md ai cheatsheets https aicheatsheets com | deep-learning artificial-intelligence machine-learning keras matplotlib scipy numpy | ai |
multiLLM | multi llm verifai implementation of invoking multiple large language models concurrently and ranking results quick start for further information look to running the multi llm application running the application inside of usage usage installation pip3 install multillm edit the config file config json to point to your google and openai api keys edit and add your credentials of each llm to the config json config json file json llms file bard py class name bard model chat bison 001 credentials path to google key json details summary strong em example google app credentials json em strong summary json client id 123489 6qr4p apps googleusercontent com client secret fx d3456 tryf0g9f9 quota project id my llm training refresh token 1 34gfh89klwe eft type authorized user details details summary strong em example openai credentials json em strong summary json organization org jc8901fdli0267 api key rt 067fgditl834 details basic example multillm c config json prompt write a python function to find a root of the function f using newton s method the above example will run the config json config json with the provided prompt details summary strong output of the above multillm command strong summary bash loading module bard finished loading module bard registered model bard bard bard object at 0x10e4e5b70 loading module gpt finished loading module gpt registered model gpt gpt gpt object at 0x10e4e5d20 loaded llms bard module bard from users verifai models bard py gpt module gpt from users verifai models gpt py calling model bard calling model gpt model chat bison 001 bard response python def newton f df x0 tol 1e 6 maxiter 100 find a root of the function f using newton s method args f the function to find a root of df the derivative of f x0 the initial guess for the root tol the tolerance for convergence maxiter the maximum number of iterations to perform returns the root of f or none if no root was found for i in range maxiter x1 x0 f x0 df x0 if abs x1 x0 tol return x1 x0 x1 return none gpt response python def newton method f f prime initial guess tol 1e 6 max iter 100 newton s method for finding the root of a function parameters f function the function for which the root is to be found f prime function the derivative of f initial guess float the initial guess for the root tol float the desired tolerance default 1e 6 max iter int the maximum number of iterations default 100 returns float the root found by newton s method or none if no root is found x initial guess for in range max iter fx f x if abs fx tol return x fpx f prime x if fpx 0 return none x fx fpx return none multillm explanation and ranking for the gpt implementation of the newton s method function newton method is well documented with clear parameter explanations and return format it also includes appropriate input validation checks and handles the case when the derivative is 0 overall it is a comprehensive and robust implementation the bard implementation of the newton s method function newton is also well documented and accepts the necessary parameters however it lacks input validation checks such as when the derivative is 0 and does not provide an explicit return value when no root is found it can be improved by addressing these limitations based on these factors i would rank gpt higher than bard in terms of the clarity completeness and robustness of the implementation details usage the multi llm application provides a powerful and efficient solution for invoking multiple large language models llms concurrently and effectively managing their outputs this section guides you through the steps required to run the application using various command line options and configuration files prerequisites before running the multi llm application ensure that you have the following prerequisites in place python 3 8 installed on your system command line usage the multi llm application can be executed from the command line using the following command structure multillm c config file prompt prompt text config file the path to the configuration file containing llm details prompt text the prompt text you want to provide to the language models config files the configuration file config json config json defines the language models and their associated parameters see config json config json for more information it follows the structure outlined below details summary strong example config json file strong summary json config multi llm llms file bard py class name bard model chat bison 001 credentials path to google key json file gpt py class name gpt model gpt 3 5 turbo credentials path to openai key json details running the application to run the multi llm application follow these steps 1 pip install multillm 2 download the config json config json file with the desired language model configurations 3 execute the following command replacing config file with the actual path to your configuration file and prompt text with the desired prompt text bash multillm c config file prompt prompt text 4 the application will run the specified language models concurrently process their responses using the provided prompt and display the results adding a new llm interface this section will guide you through the process of adding a new llm by extending the basellm class and customizing it to fit the requirements of your specific language model follow these steps to add an new llm interface 1 start by creating a new python file in your project directory newllm py or within the appropriate package where you ll define a new class that inherits from basellm implement the required methods get response and get content the get response method should execute your language model with the provided prompt and the get content method should extract relevant content from the response see example below details summary example newllm py summary python import os sys from multillm basellm import basellm from multillm prompt import prompt add additional imports here newllm interface the newllm class extends the basemodel class and overrides the get response method providing an implementation class newllm basellm attributes and init method def init self kwargs add values here directly or if kwargs are specified they are taken from the config file defaults class name newllm model newllm bison 06 credentials path to my key json call api and get response from newllm def get response self prompt implement your language model interaction here access credentials file from self credentials access model from self model access class name from self class name response generated response from newllm model based on prompt return response parse and filter raw response from newllm and return text code content def get content self response implement content extraction from the response content extracted content from response return content details 2 add newllm in config json file in the llms section details summary strong add newllm to the config json file strong summary json config multi llm llms file full path newllm py class name newllm model chat bison 001 credentials path to google key json details 3 call multillm to run your new llm or embedd it in your code multillm c config json prompt wite a function to sort a billion integers 4 optional embedd newllm py in your code you can now use your custom newllm class in your application code instantiate it call its methods and integrate it into your application s workflow python custom llm newllm model custom model credentials your credentials prompt generate something amazing response custom llm get response prompt content custom llm get content response print content by extending the provided basellm class you can easily create custom language model implementations tailored to your project s needs this structured approach ensures consistency and modularity in your codebase allowing you to focus on the unique aspects of your language model while leveraging the foundational structure provided by basellm example of the gpt interface included with multillm release details summary strong example model gpt py strong summary python import os sys import openai import json from multillm basellm import basellm from multillm prompt import prompt openai gpt interface the gpt class extends the basemodel class implements the required methods get response and get content the get response method takes a response parameter and returns the content of the first response in the given response object class gpt basellm implement here def init self kwargs add values here directly or if kwargs are specified they are taken from the config file defaults class name gpt model gpt 3 5 turbo credentials key json get content required method def get content self response get the text from the response of an llm e g openai returns the following response this method should return the content choices message content def binary sort arr return response choices 0 message content get response required method call openai api def get response self prompt setup prompt for api call messages messages append role prompt get role content prompt get string if prompt context messages append role prompt get role content prompt get context read credentials file specified in the config json setup for openai if not os path exists self credentials print error multi llm could not find openai credentials 0 format self credentials return open the file for reading try with open self credentials r as file load the json data from the file data json load file openai organization data organization openai api key data api key except exception as e print multi llm error could not load credentials 0 1 format self credentials str e return do api call response openai chatcompletion create model self model messages messages if response return self get content response else return response details config json using the config json file the config json file offers a convenient way to configure and load multiple language models using the multi llm framework this section will guide you through the process of creating and utilizing a config json file to load and use specific language models in your application configuration setup to get started follow these steps to configure your config json file 1 create a configuration file create a new file named config json in your project directory or the desired location 2 configure llms define the language models you want to use within the llms array each model configuration includes details such as the python file containing the model implementation class name model name and credentials file path json config multi llm llms file bard py class name bard model chat bison 001 credentials path to google key json file gpt py class name gpt model gpt 3 5 turbo credentials path to openai key json loading models using multillm after creating the config json file you can use the multi llm framework to load and utilize the configured models in your application follow these steps 1 instantiate multi llm create an instance of the multi llm class and provide the path to your config json file python from multi llm import multi llm specify the path to your config json file config path path to config json instantiate multi llm multi llm multi llm config config path 2 run models use the run method to run the loaded models and process their responses provide a prompt and an optional action chain if needed the responses from each model will be returned in a dictionary python prompt translate this sentence action chain none you can define an action chain if required responses multi llm run prompt action chain print responses action class this is the interface class which we use to operate on the output while still in parallel action class instances are define by the user and can be chained indefinitely with other actiion instances there are two methods that are used to interface with the class apply and then the first apply is what is used internally to call the methods we register registration is as follows python write an interfacing function a simple in out def capitalize data data data upper return data def lower data data data lower return data create the respective objects action1 action operation capitalize action2 action operation lower create the chain of actions action chain action1 then action2 what we did was create some actions that are simple i o operations on data we can then chain them together using the then method mentioned above the order of operations for then is left to right in this case action1 will go first then action2 these actions can be tailored to your own specification since the actions are serial you can specify the information that is going to be passed into the function and what information will be returned after you have created the action chain you can pass this into the multillm run method and run action chain the action chain is a core component of processesing llm output in the provided example py examples example py we see the first action defined is for processing the llm response and extracting the code alone from the response this could be a first of many steps what could follow could be saving the code to the file or extracting information through the ast module the actions are meant to be ran on each of the model s outputs so they should be generalized for use rank class the rank class is identical in functionality to the action class though the use is different while the action class is used to accept and modify data in each of the models the rank class purpose is to modify the final combined output of the llms this output is stored in a dictionary keyed by the model s names the rank class s methods should be written to take this data and operate on it python write an interfacing function a simple print def print llms dictionary for key val in dictionary items print key val create rank instances rank object rank operation print llms running the llm assuming an instance of multillm named mllm results mlllm run prompt action chain rank object in the above code we are doing very similar actions as those seen above the methodoly is the same in this case we only have a single object so instead of creating a rank chain we simply pass in our single instantiated object architecture high level overview alt images multi llm 1 png multillm class this is the highest level here we can instantiate multillm objects using either config files see config files config files or manually instantiating a custom or hosted llm in this class we call multiple llms concurrently and then we can operate on the results of each in parallel using the action class action class the multillm python code provides a versatile framework for managing and orchestrating multiple language models llms within a single application this code is designed to enhance the efficiency of working with language models by enabling concurrent execution response processing and model loading from configuration files the key features and components of the code include concurrent model execution the code allows you to run multiple language models concurrently facilitating efficient utilization of computational resources this is particularly useful for scenarios that involve processing multiple prompts or tasks simultaneously action chain processing the framework supports the concept of action chains which enable you to preprocess model responses using a sequence of predefined actions this empowers you to refine and enhance the output generated by the language models model loading from configuration you can load llms from a configuration file this json based configuration includes essential details about each model such as the model class associated credentials and file paths the code can dynamically load these models making it easy to add new models or modify existing ones without altering the core codebase redis integration the code features optional integration with a redis instance it checks for a successful redis connection and adjusts its behavior accordingly if redis connectivity is not established the code gracefully handles the situation by setting a flag that reflects the absence of a redis connection simplified model registration the code includes a straightforward method to register models within the framework this allows for the inclusion of custom llm implementations while ensuring that the models are appropriately organized and accessible for execution by using the multillm python code developers can streamline their interactions with multiple language models seamlessly integrating them into various applications or projects the code promotes modularity reusability and parallelism in working with language models ultimately enhancing the user experience and productivity basellm basellm is designed to serve as the basis for implementing various language model classes this basellm class encapsulates essential attributes and methods necessary for interfacing with language models the code establishes a structured foundation for building specific language model implementations and harmonizes their interaction within a larger application context key features and components of the code include attributes for language models the basellm class declares a set of attributes such as model roles messages temp api key max tokens and args that are pertinent to language models these attributes are meant to be customized and adapted as needed for specific model implementations customizable initialization the init method in the basellm class facilitates flexible instantiation of model instances by allowing the specification of custom values via keyword arguments it enables the convenient configuration of attributes like name credentials model and class name placeholder methods the basellm class defines two placeholder methods get response and get content the get response method is designed to receive a prompt object and run the associated language model with the provided prompt the actual implementation of this method is expected to be customized in derived classes to perform the model specific interactions similarly the get content method is meant to be implemented by deriving classes providing an interface to extract relevant content from model responses structured framework the code encapsulates a structured framework that abstracts common functionalities of language models by inheriting from the basellm class developers can focus on implementing model specific interactions while leveraging the established structure for attribute handling and method placeholders basellm aims to streamline the development of specific language model implementations by providing a consistent structure and standardized attributes developers can extend this base class to create custom language model classes that seamlessly integrate into the broader application ecosystem this modular approach promotes reusability maintainability and consistent design patterns when working with various language models contribution you can contribute by extending the models located in models models see the basellm baselmm section for more information on the necessary mechanisms for extending the basellm class for further information contact ethansaurusrex https github com ethansaurusrex | api bard chatgpt large-language-models llama2 | ai |
cloud-engineering-series | cloud engineering series part one introduction to iac adn terraform | cloud |
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Mobile-JavaScript-Application-Development | mobile javascript application development this repository contains the code of the mobile javascript application development book by adrian kosmaczewski published by o reilly cover of mobile javascript application development by adrian kosmaczewski at o reilly http akamaicovers oreilly com images 0636920025252 cat gif cover of the book installation run the install sh script to download all the required libraries from their respective repositories phonegap kitchen sink the phonegap chapter of the book references the phonegap kitchen sink project 3 by jens christian fischer buy the book you can buy a copy of the book at these locations o reilly 1 o reilly safari books online 13 ibooks store 14 amazon com 2 amazon co uk 12 amazon ca 6 amazon de 7 amazon fr 8 amazon co jp 9 amazon es 10 amazon it 11 amazon cn 15 barnes and noble http www barnesandnoble com w mobile javascript application development adrian kosmaczewski 1112079017 thalia ch http www thalia ch shop buch buecher 2 mehrvonartikel mobile javascript application development adrian kosmaczewski isbn1 4493 2785 0 id31941323 html license copyright c 2012 adrian kosmaczewski all rights reserved redistribution and use in source and binary forms with or without modification are permitted provided that the following conditions are met redistributions of source code must retain the above copyright notice this list of conditions and the following disclaimer redistributions in binary form must reproduce the above copyright notice this list of conditions and the following disclaimer in the documentation and or other materials provided with the distribution this software is provided by the copyright holders and contributors as is and any express or implied warranties including but not limited to the implied warranties of merchantability and fitness for a particular purpose are disclaimed in no event shall the copyright holder or contributors be liable for any direct indirect incidental special exemplary or consequential damages including but not limited to procurement of substitute goods or services loss of use data or profits or business interruption however caused and on any theory of liability whether in contract strict liability or tort including negligence or otherwise arising in any way out of the use of this software even if advised of the possibility of such damage 1 http shop oreilly com product 0636920025252 do 2 http www amazon com mobile javascript application development kosmaczewski dp 1449327850 3 https github com jcfischer pgkitchensink 6 http www amazon ca mobile javascript application development kosmaczewski dp 1449327850 7 http www amazon de mobile javascript application development kosmaczewski dp 1449327850 8 http www amazon fr mobile javascript application development kosmaczewski dp 1449327850 9 http www amazon co jp mobile javascript application development kosmaczewski dp 1449327850 10 http www amazon es mobile javascript application development kosmaczewski dp 1449327850 11 http www amazon it mobile javascript application development kosmaczewski dp 1449327850 12 http www amazon co uk mobile javascript application development kosmaczewski dp 1449327850 13 http my safaribooksonline com 9781449327842 portal oreilly cid orm cat readnow 9781449327842 14 http itunes apple com us book mobile javascript application id537701148 mt 11 15 http www amazon cn mobile javascript application development kosmaczewski adrian dp 1449327850 | front_end |
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System-Design | system design picking the right architecture picking the right battles managing trade offs p align center img src images title png p what are system design questions in this section i ll talk about the questions which require the interviewee to design a high level architecture for some sort of software system this can be a web facing service a restful api a peer to peer desktop app and so on the exact type of question will most likely vary depending on the specifics of the company you interview at some examples i can give a few examples of such questions design a url shortening service like bit ly how would you implement the google search design a client server application that allows people to play chess with one another how would you store the relations in a social network like facebook and implement a feature where one user receives notifications when their friends like the same things as they do hopefully these example questions give you some idea of what i will be talking about the web is full of many other examples in addition to that the book cracking the coding interview https github com black shadows cracking the coding interview has a small section offering some more such questions don t panic these questions may seem intimidating at first after all how does one design google search in 20 30 minutes it took many smart people several years to do that properly don t worry no one really expects that from you the idea of these questions is to have a discussion about the problem at hand what s important for the interviewer is the process which you use to tackle the problem the typical outcome of such a discussion is a high level architecture addressing the goals and constraints in the question perhaps the interviewer will choose one or more areas where they will want to discuss bottlenecks and other common problems remember that there is no one right answer a system can be built in different ways the important thing is to be able to justify your ideas this is somewhat different from the algorithm design questions as discussed here at interviewbit https github com black shadows interviewbit topicwise solutions and leetcode https github com black shadows leetcode topicwise solutions finally keep in mind that the discussion about the same system design problem could go in different directions depending on the goals of the interviewer they may be willing to see how you create a high level architecture covering all aspects of the system or rather they could be more interested in looking at a few specific areas and diving deeper into them in any case you should have a strategy for how to approach different situations we will look into such strategies in the next sections our approach similar to the algorithmic questions i believe that system design questions require a combination of the right strategy and knowledge by strategy i mean a way to approach the problem at an interview i ve seen good candidates fail not because they lack the knowledge but because they cannot focus on the right things while discussing a problem because of that in the next few sections i will present our strategy for approaching system design questions at tech interviews in addition to that i ve collected useful online resources which will help you update your knowledge of software systems design quick overview over time i ve identified two major challenges most candidates face when it comes to system design questions candidates either approach questions in a chaotic way and get ratholed or lack solid understanding of how to properly design architectures that scale fixing these two problems is going to be our focus by the time you ve finished all sections you ll be exceptionally well equipped to tackle any system design question the system design process first things first i ll kick off by replacing chaos with a structured approach to system design the system design process described in the next section takes care of that as it describes all the steps you need to follow from hearing the problem to declaring it solved designing scalable architectures with the right process in place i ll move on to destroying the second obstacle to your dream job i ll spend a significant amount of time building up your knowledge and intuition around designing scalable architectures scalability is the 4th step of the system design process i am spending a disproportionate amount of time on it simply because this is where candidates struggle the most to beef up your scalability knowledge i ve selected some of the best readings http book mixu net distsys single page html and videos https www codekarle com available online they ll teach you the real life practical underpinnings of designing systems that scale examples of some of the internet s most popular websites instagram tripadvisor salesforce com stackoverflow and many others step 1 constraints and use cases just like algorithm design system design questions will also most likely be weakly defined consider the question about the url shortening service design a url shortening service like bit ly there are so many things that are unclear about it without knowing more it will be impossible to design an appropriate solution actually many candidates forget about this and start designing a solution immediately don t make this mistake the very first thing you should do with any system design question is to clarify the system s constraints and to identify what use cases the system needs to satisfy spend a few minutes questioning your interviewer and agreeing on the scope of the system many of the same rules we follow while building algorithms apply here as well usually part of what the interviewer wants to see is if you can gather the requirements about the problem at hand and design a solution that covers them well never assume things that were not explicitly stated for example the url shortening service could be meant to serve just a few thousand users but each could be sharing millions of urls it could be meant to handle millions of clicks on the shortened urls or dozens the service may have to provide extensive statistics about each shortened url which will increase your data size or statistics may not be a requirement at all you will also have to think about the use cases that are expected to occur your system will be designed based on what it s expected to do don t forget to make sure you know all the requirements the interviewer didn t tell you about in the beginning step 2 abstract design once you ve scoped the system you re about to design you should continue by outlining a high level abstract design the goal of this is to outline all the important components that your architecture will need you can tell the interviewer that you would like to do that and draw a simple diagram of your ideas sketch your main components and the connections between them if you do this very quickly you will be able to get feedback if you are moving in the right direction of course you must be able to justify the high level design that you just drew don t get lured to dive deep into some particular aspect of the abstract design not yet rather make sure you sketch the important components and the connections between them justify your ideas in front of the interviewer and try to address every constraint and use case usually this sort of high level design is a combination of well known techniques which people have developed you have to make sure you are familiar with what s out there and feel comfortable using this knowledge in this section i will assume that you have enough experience to design such a high level system my goal is to focus more on the next steps where i will talk mainly about scalability and about removing bottlenecks if you feel like a complete beginner in system design perhaps it will be very useful for you to first look at a book on the topic or take advantage of some of the resources i ve shared in the sections above step 3 understanding bottlenecks most likely your high level design will have one or more bottlenecks given the constraints of the problem this is perfectly ok you are not expected to design a system from the ground up which immediately handles all the load in the world it just needs to be scalable in order for you to be able to improve it using some standard tools and techniques now that you have your high level design start thinking about what bottlenecks it has perhaps your system needs a load balancer and many machines behind it to handle the user requests or maybe the data is so huge that you need to distribute your database on multiple machines what are some of the downsides that occur from doing that is the database too slow and does it need some in memory caching these are just examples of questions that you may have to answer in order to make your solution complete it may be the case that the interviewer wants to direct the discussion in one particular direction then maybe you won t need to address all the bottlenecks but rather talk in more depth about one particular area in any case you need to be able to identify the weak spots in a system and be able to resolve them remember usually each solution is a trade off of some kind changing something will worsen something else however the important thing is to be able to talk about these trade offs and to measure their impact on the system given the constraints and use cases defined once you ve outlined the core bottlenecks you see you can start addressing them in the next step step 4 scaling your abstract design once you re ready with your high level design and have made sure that the interviewer is ok with it you can dive into making it more detailed usually this means making your system scale i ve devoted the next sections of this discussion to the topic of scalability i will first cover some theoretical fundamentals and then look at many real life examples of scalable architectures finally i ll wrap things up with several of the core principles for discussing scalability at interviews scalability fundamentals now that you ve designed a solid abstract architecture the next step is to take it to scale if you ve never built a large scale system this task may seem a little daunting where do you start there is a common set of scalability principles that you need to know knowing what they are understanding how they are used and being able to discuss their pros and cons is what scalability at interviews is all about how do you build up that intuition the first thing i d recommend you to do is watch this video https www youtube com watch v w9f d3oy4 ab channel jorgescott in it professor david malan from harvard is teaching a huge part of the intuition you will need to have when it comes to scalability so start here watch the video and make sure you understand it well after watching it you should have a good fundamental understanding of the following concepts vertical scaling horizontal scaling caching load balancing database replication database partitioning next i recommend reading this great 4 post scalability for dummies tutorial part 1 https www lecloud net post 7295452622 scalability for dummies part 1 clones part 2 https www lecloud net post 7994751381 scalability for dummies part 2 database part 3 https www lecloud net post 9246290032 scalability for dummies part 3 cache part 4 https www lecloud net post 9699762917 scalability for dummies part 4 asynchronism it reiterates on some of the topics mentioned above but also introduces several important new concepts using nosql instead of scaling a relational database being asynchronous you would also know how to deal with the two major bottlenecks handling a lot of users and handling a lot of data finally you may want to read this tutorial on database sharding http highscalability com blog 2009 8 6 an unorthodox approach to database design the coming of the html it s a very common and powerful way of database scaling as you learned from prof malan s lecture scalability examples the awesome thing about scalability is that it s all around us if you want to work on an exciting and successful product or service by definition it s going to have to operate at scale many of the web s largest websites have been very open about how they scale it s extremely interesting to look under the hood of instagram salesforce com tripadvisor twitter google and many many others that s exactly what we ll be doing in this section the goal is to show you how the theoretical principles from the previous section are applied in practice as well as to introduce you to some of the real life technologies many companies use nowadays let s get going here are some real life architectures i d recommend you read analyze and understand product question img src images uber jpeg width 70 height 50 how uber had to scale fast about breaking your service into many microservices spread across many repos http highscalability com blog 2016 10 12 lessons learned from scaling uber to 2000 engineers 1000 ser html img src images facebook jpeg width 70 height 50 how facebook handles 800 000 simultaneous viewers on a live stream http highscalability com blog 2016 6 27 how facebook live streams to 800000 simultaneous viewers html img src images twitter jpeg width 70 height 50 how twitter handles 3 000 image uploads per second and why the old ways it used would not work nowadays http highscalability com blog 2016 4 20 how twitter handles 3000 images per second html img src images salesforce jpeg width 70 height 50 a relatively short example from salesforce http highscalability com blog 2013 9 23 salesforce architecture how they handle 13 billion transacti html img src images espn png width 70 height 50 another awesome and thorough example this time from the digital media industry http highscalability com blog 2013 11 4 espns architecture at scale operating at 100000 duh nuh nuhs html img src images twitter jpeg width 70 height 50 finally some good example of twitter subcomponents storing data http highscalability com blog 2011 12 19 how twitter stores 250 million tweets a day using mysql html and timeline http highscalability com blog 2013 7 8 the architecture twitter uses to deal with 150m active users html img src images google png width 70 height 50 how google store and manage huge amount of data http highscalability com google architecture img src images youtube png width 70 height 50 how youtube distribute their most popular content and priortize resources http highscalability com youtube architecture img src images stackoverflow png width 70 height 50 how stackoverflow handles 16 million page views and 3 million unique visitors a month http highscalability com blog 2009 8 5 stack overflow architecture html don t worry if you don t understand everything many of the posts contain lots of nitty gritty details which while priceless to know on your job are not requirements at interviews try to focus on the shared principles used and keep track of the lessons learned by these folks as you read the posts you ll start noticing common technologies and patterns appear as you do make sure you do some research on each frequently seen technology try to write down what problem it solves what its alternatives are and what some common pros and cons may be one good way to research the alternatives to technology is to type its name in google followed by the text vs and see what shows up in the google suggest box for example if you typed rabbitmq vs you d get entries like rabbitmq vs activemq rabbitmq vs redis rabbitmq vs msmq rabbitmq vs kafka which is a pretty good list to get you started the goal of all this reading other than having tons of fun is to develop practical knowledge about what works and what doesn t work in the real world after reviewing a bunch of these architectures and seeing where they agree or disagree you d be very well positioned to move on to the next step scalability warp up alright at this point you already have a solid theoretical and practical understanding of system design in this section i ll wrap things up and put them in the context of technical interviews everything is a tradeoff this is one of the most fundamental concepts in system design hopefully at this point this is not a surprise to you if you ve looked at the real life architectures you saw that there rarely is one perfect way to do things each company ends up with a different architecture designing a scalable system is an optimization task there are tons of constraints time budget knowledge complexity technologies currently available etc and you need to build the best thing that fits those constraints every technology every pattern is great for some things and not so great for others understanding these pros and cons the advantages and disadvantages is key remember there is no one optimal system design sure there are best practices you can use but at the end of the day it all boils down to balancing between time to market system complexity cost of development cost of maintenance availability and many other things being able to understand and discuss these trade offs is what system design and thus system design questions is all about in your preparation don t try to find silver bullets instead focus on what each scalability pattern is good for what its shortcomings are and why people prefer it over other patterns putting it all together and staying up to date at this point the most useful thing you could do is come up with a one or two pager that contains the scalability lessons you ve learned finally you d be well served throughout your professional career to stay up to date on how scalability evolves for example 10 years ago there were no amazon web services and companies were forced to manage their infrastructure in house nowadays using services like ec2 rds s3 elastic mapreduce etc you can build a giant company so while aws didn t change the fundamental scalability principles it did change the landscape of technologies people need to be familiar with when scaling thus staying up to date is quite important or else you d be reinventing the wheel at the interview so what should you do at your interview first of all follow the system design process you already know how to apply it don t skip steps don t make assumptions start broad and go deep when asked second keep in mind that system design questions serve as an idea exchange platform be prepared for discussions about tradeoffs about pros and cons be prepared to give alternatives to ask questions to identify and solve bottlenecks to go broad or deep depending on your interviewer s preferences don t get defensive whenever your interviewer challenges your architectural choices acknowledge that rarely an idea is perfect and outline the advantages and disadvantages of your choice be open to new constraints to pop up during the discussion and to adjust your architecture on the fly most of all have fun dreaming up architecture is a very stimulating mental process enjoy it and stay positive you re already equipped with the right knowledge just apply it during your interview and you ll do well how to practice practicing system design questions is more difficult than practicing algorithm design questions for algorithm design there are online judges and courses like the one from hiredintech https www hiredintech com courses algorithm design that combine problem banks with sample solutions and automated graders that can tell you exactly how good your solution is this is simply priceless there is no such thing as system design so what do you do i have several suggestions in the following lessons in this section also there are some more useful resources online that you can take a look at introduction https lethain com introduction to architecting systems for scale basics of system design https weifoo gitbooks io systemdesign content concepts you should know https www freecodecamp org news systems design for interviews solved examples of system design http blog gainlo co index php category system design interview questions solve with friends look at the massive systems you use every day developed by the companies you are interviewing for what systems did these companies have to design create a list of the fundamental system design questions that bubble up in your brain here are a few to get you started twitter real time feed of the tweets by the people you re following google instantly returning the pages matching any search query search storing and serving massive amounts of video data youtube aggregating the world s news by topic google news facebook serving massive amounts of photos start by compiling a list of 10 to 20 of these questions then pick one and try to come up with an efficient design make sure you follow the process discussed in the previous sections once you re ready find a knowledgeable friend or coworker go to a meeting room and start discussing ideas it d be tons of fun and you ll learn a lot from the process don t spend hours initially limit your time per question to one hour and ultimately try to fit every question in 20 to 30 minutes if you can t find a friend coworker go to a site like highscalability that contains tons of examples of real life architectures and compare what you conjured up to what these companies actually did you d be surprised how many of the top websites architectures are widely available keep in mind that these systems were designed by multiple people over multiple months so don t expect to be able to come up with every low level decision they made focus on the high level stuff mock interviews while practicing in isolation with a friend is very useful up to a point at some stage in your preparation process it d be time to face the music you need to get actual real life interview experience under your belt mock interviews are a fantastic way to practice system design questions system design questions are all about organic discussions around trade offs try to find an unbiased and knowledgeable person and do several interviews with them it can be a friend a colleague or you could use a paid service paid mock interviews allow you to practice being comfortable discussing ideas with a stranger working under the stress of time pressure and guarantee objective feedback and if the person providing it is skilled at interviewing you d get lots of action items and high quality advice if you choose to do it with a friend make sure they stay impartial and give you honest feedback friends tend to be too nice to us the nice thing about doing mock interviews with friends is that they are very generous with their time so you can do multiple interviews with them at no cost but make sure you choose a skilled interviewer there is little value in doing mock interviews with someone who has poor interviewing skills nowadays is it also possible to do mock interviews with other people online for free one service that i found useful for this is pramp com https www pramp com utm source hiredintech utm medium website link utm campaign hiredintech you could use it for your system design interview preparation no matter if you choose paid services or interviewing with friends mock interviews are going to be highly useful to you when it comes to system design questions make sure you do at least a few of those prior to your interview summary a strong process is crucial to successfully solve system design questions i broke it down into four steps scope the problem don t make assumptions ask questions understand the constraints and use cases sketch up an abstract design that illustrates the basic components of the system and the relationships between them think about the bottlenecks these components face when the system scales address these bottlenecks by using the fundamentals principles of scalable system design when it comes to system design it s incredibly useful to review real life architectures as you do this make sure you pay attention to what technologies are used go ahead and research each new technology and see what problem it solves what its alternatives are where it excels and where it fails take note of the common patterns you see and how they relate to the scalability theory you learned in the previous section read through the lessons learned they are a very quick way to learn from other people s battle scars you now know how to approach any system design question you first build a high level architecture by identifying the constraints and use cases sketching up the major components and the relationships between them and thinking about the system s bottlenecks you then apply the right scalability patterns that will take care of these bottlenecks in the context of the system s constraints we discussed several strategies for practicing system design questions by combining discussing solutions with friends or coworkers with reading about scalable real world systems and doing mock interviews you d be able to develop strong system design chops my recommendation is to start by working on system design questions yourself then move on to discussing designs with friends to finally doing mock interviews good luck and enjoy if you have any doubts regarding system design feel free to contact me abhisheksharma 0517 gmail com | os |
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scrapy-development-docker | scrapy development docker web scraping development docker container this container includes python selenium beautifulsoup scrapy scrapyjs https github com scrapinghub scrapy splash boto3 build the image use docker build to buid your web scraping container docker build t scrapy start the container use v to mount your local development spider code docker run v documents development opt dev it scrapy bin bash | front_end |
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STM32F429_Discovery_FreeRTOS_9 | stm32f429 discovery freertos 9 0 install ubuntu 16 04 2 desktop amd64 run commands sudo apt get update sudo apt get upgrade sudo apt get install build essential git sudo apt get install gcc arm none eabi gdb arm none eabi mkdir work cd work git clone https github com cbhust stm32f429 discovery freertos 9 git 1 qemu qemu system gnuarmeclipse qemu stm32f4 eclipse https github com gnu mcu eclipse qemu releases tag gae 2 8 0 20161227 gnuarmeclipse qemu debian64 2 8 0 201612271623 dev tgz work path cd work tar xvf gnuarmeclipse qemu debian64 2 8 0 201612271623 dev tgz chmod r w qemu export path work qemu 2 8 0 201612271623 dev bin path qemu qemu system gnuarmeclipse version 2 8 0 2 projects demo1 make hello rtos elf qemu system gnuarmeclipse stm32f4 freertos portable arm cm4f arm cm3 3 qemu projects demo1 qemu sh bin bash qemu system gnuarmeclipse verbose verbose board stm32f429i discovery mcu stm32f429zi d unimp guest errors image hello rtos elf semihosting config enable demo1 qemu sh qemu hello rtos elf gui 4 gdb projects demo1 qemu gdb gdb tcp 1234 s qemu gdb arm none eabi gdb gdb gdb target remote localhost 1234 gdb continue qemu gui 5 trace projects demo1 freertos trace stm32 st link utility hello rtos hex stm32f429i discovery stm32 st link utility 0x20000000 0x20030000 trace data bin https percepio com tz freertostrace tracealyzer for freertos tracealyzer for freertos trace data bin freertos | os |
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IOTrackerOnWeb | iotrackeronweb an http file i o tracker tweak for ios just inject the dylib to target app and view log on http iphone local 8080 how to build sh make libcocoahttpserver a cd cocoahttpserver make make headers cd make tweak make clean package make install theos device ip iphone local usage change iotracker plist https github com upbit iotrackeronweb blob master iotracker plist for tweak inject process iotracker will listen on 8080 so access http ip address 8080 in chrome screenshot https raw github com upbit iotrackeronweb master screenshot png | theos tweak | server |
natural-language-processing | natural language processing course resources this github contains practical assignments for natural language processing course by higher school of economics https www coursera org learn language processing in this course you will learn how to solve common nlp problems using classical and deep learning approaches from a practical side we expect your familiarity with python since we will use it for all assignments in the course two of the assignments will also involve tensorflow you will work with many other libraries including nltk scikit learn and gensim you have several options on how to set it up 1 running on google colab google has released its own flavour of jupyter called colab which has free gpus here s how you can use it 1 open https colab research google com click sign in in the upper right corner use your google credentials to sign in 2 click github tab paste https github com hse aml natural language processing and press enter 3 choose the notebook you want to open e g week1 week1 multilabelclassification ipynb 4 click file save a copy in drive to save your progress in google drive 5 if you need a gpu click runtime change runtime type and select gpu in hardware accelerator box 6 execute the following code in the first cell that downloads dependencies change for your week number python wget https raw githubusercontent com hse aml natural language processing master setup google colab py o setup google colab py import setup google colab please uncomment the week you re working on setup google colab setup week1 setup google colab setup week2 setup google colab setup week3 setup google colab setup week4 setup google colab setup project setup google colab setup honor 7 if you run many notebooks on colab they can continue to eat up memory you can kill them with pkill 9 python3 and check with nvidia smi that gpu memory is freed known issues no support for ipywidgets so we cannot use fancy tqdm progress bars for now we use a simplified version of a progress bar suitable for colab blinking animation with ipython display clear output it s usable but still looking for a workaround if you see an error no module named common make sure you ve uncommented the assignment specific line in step 6 restart your kernel and execute all cells again 2 running locally two options here 1 use the docker container of our course it already has all libraries that you will need the setup for you is very simple install docker application depending on your os download our container image run everything within the container please see this detailed docker tutorial docker tutorial md 2 manually install all the libraries depending on your os each task contains a list of needed libraries in the very beginning if you use windows macos you might find useful anaconda distribution which allows to install easily most of the needed libraries however some tools like starspace for week 2 are not compatible with windows so it s likely that you will have to use docker anyways if you go for these tasks it might take a significant amount of time and resources to run the assignments code but we expect that an average laptop is enough to accomplish the tasks all assignments were tested in the docker on mac with 8gb ram if you have memory errors that could be caused by not tested configurations or inefficient code consider reporting these cases or double checking your code if you want to run the code of the course on the aws machine we ve prepared the aws tutorial here aws tutorial md | natural-language-processing | ai |
android-kubernetes-blockchain | create an android app with blockchain integration warning this repository is no longer maintained warning this repository will not be updated the repository will be kept available in read only mode refer to https developer ibm com patterns category blockchain for other blockchain code patterns in this code pattern we will create an android app that tracks the user s physical steps with blockchain capabalities using kubernetes the blockchain framework implementation used is hyperledger fabric the users are registered to the blockchain network anonymously and get rewarded with some coins for the steps they take the users can trade their coins for some swag and these transactions are executed in the blockchain network this android app was used in kubecon europe 2018 this code pattern is for developers who wish to provide data anonymity and security to their users their users will be more confident to use their app if it gives them more control over their privacy the developers can also extend the pattern to use the backend from different platforms when you have completed this code pattern you will understand how to build a native android app and use google fit for its steps data deploy a blockchain network in kubernetes integrate the android app with the blockchain network flow docs architecture png 1 the rest api is how the mobile app will interact with the blockchain network the api will acknowledge the request and the mobile app will receive a unique key random numbers and letters which will be used to get the blockchain s response later 2 the api just stores the request in a queue in rabbitmq the queue has 2 channels which are for the user fitcoin org and the seller shop org the requests can either be user enrollment query data from the blockchain network number of kubecoins of a user products that are for sale contracts etc invoke or perform a transaction send steps to receive kubecoins claim a product complete a transaction etc 3 the execution workers use the hyperledger fabric node js sdk to perform above requests they are listening to the requests from rabbitmq 4 the workers send the requests to the blockchain network and are then processed the blockchain network uses nfs to persist the ledger and state database 5 the workers receive the response and then persists it in the redis database with the unique key from 1 6 the mobile app will continue to wait for the blockchain s response results that should be in the redis database this is where the unique key is used the mobile app will query the redis database with the unique key 7 the registration microservice is used to create a user or update the user s steps when the blockchain network enrolls a user this service uses the user id assigned by the blockchain network 8 when a user is registered it calls a cloud function to generate a random name and avatar for the user 9 the data from the microservices are persisted in a mongodb this is where the user s data steps name and avatar and mobile assets booklet articles in the first view of mobile app are persisted 10 the mobile assets microservice is used to query the mongodb to get dynamic data for the mobile app the booklet in the first view uses the database for its content 11 the leaderboard microservice is used to get the standings of the users summary the first time the user opens the app he gets anonymously assigned a unique user id in the blockchain network they also get assigned a random avatar and name which will be stored in mongodb this data will be used for the leaderboard the 3 microservices leaderboard mobile assets registration outside of the blockchain network are node js web apps to get data from the monodb as users walk around their steps will be sent to the blockchain network and they will be rewarded with kubecoins these coins can be used in the blockchain network to trade assets the assets we have are some swag stickers bandanas etc for the kubecon conference users can see and claim them using the app once they claim a product they ll get a contract id they ll show the contract id to the seller us and we will complete and verify the transaction in our dashboard and give them the swag the users can also check how they are doing with their steps compared to other people in the standings view in the mobile app or in the kubecoin dashboard included components ibm cloud kubernetes service https console bluemix net docs containers container index html ibm cloud kubernetes service manages highly available apps inside docker containers and kubernetes clusters on the ibm cloud hyperledger fabric v1 0 https www hyperledger org projects fabric an implementation of blockchain technology that is intended as a foundation for developing blockchain applications or solutions for business compose for mongodb https www ibm com cloud compose mongodb mongodb with its powerful indexing and querying aggregation and wide driver support has become the go to json data store for many startups and enterprises compose for rabbitmq https www ibm com cloud compose rabbitmq rabbitmq is a messaging broker that asynchronously communicates between your applications and databases allowing you to keep seperation between your data and app layers compose for redis https www ibm com cloud compose redis an open source in memory data structure store used as a database cache and message broker cloud functions https www ibm com cloud functions execute code on demand in a highly scalable serverless environment featured technologies blockchain https www ibm com blockchain distributed database maintaining a continuously growing list of secured records or blocks container orchestration https www ibm com cloud container service automating the deployment scaling and management of containerized applications serverless https www ibm com cloud functions an event action platform that allows you to execute code in response to an event databases https en wikipedia org wiki ibm information management system 22full function 22 databases repository for storing and managing collections of data prerequisites create a kubernetes cluster with ibm cloud kubernetes service https console bluemix net docs containers cs cli install html cs cli install to deploy in cloud install node js https nodejs org install docker https www docker com by following the instructions here https www docker com community edition download for your preferrerd operating system you would need docker if you want to build and use your own images install android studio https developer android com studio steps 1 clone the repo git clone https github com ibm android kubernetes blockchain 2 create ibm cloud services create the following services ibm cloud kubernetes service https console bluemix net containers kubernetes catalog cluster compose for mongodb https console bluemix net catalog services compose for mongodb compose for rabbitmq https console bluemix net catalog services compose for rabbitmq compose for redis https console bluemix net catalog services compose for redis 3 configure the blockchain network get your compose for rabbitmq and redis credentials from the main page of each respective service in your ibm cloud dashboard docs rabbit credentials png docs redis credentials png in containers blockchain configuration config js modify the values for rabbitmq and redis starting on line 12 with your own credentials chaincodepath bcfit rabbitmq amqps admin qwerty portal ssl334 23 bmix dal yp abc10717 6f73 4f63 b039 a1d2485c1566 devadvo us ibm com composedb com 38919 bmix dal yp abc10717 6f73 4f63 b039 a1d2485c1566 redisurl redis admin qwerty sl us south 1 portal 23 dblayer com 38916 configure the yaml files to use your mongodb instance get the certificate and url in your compose for mongodb dashboard mongo credentials https github com ibm pattern utils blob master compose dbs mongo url string png raw true add the mongodb url in leaderboard api yaml mobile assets yaml registeree api yaml in the environment variable of mongodb url env name mongodb url value mongodb admin qwerty sl us south 1 po build and push the images in docker hub the provided script will help you build and push the images quicker this will also modify the kubernetes yaml files to use your your newly built images you will need to be logged in using docker login buildandpushimages sh your dockerhub username 4 deploy the blockchain network in kubernetes deploy the microservices in kubernetes the provided script will help you run kubectl commands you will need to point your kubectl cli to your iks https console bluemix net docs containers cs cli install html cs cli configure deploynetwork sh test the blockchain network using its api client kubectl get svc rabbitclient api name cluster ip external ip port s age rabbitclient api 172 21 40 201 169 61 17 000 3000 30726 tcp 14m use the external ip of the service to do a curl request export url http 169 61 17 000 3000 curl h content type application json x post d type enroll queue user queue params url api execute you should get something like this status success resultid 7f90764a 8660 45f2 904d 47d8fb87a900 check the result using the resultid you got above you should get a user id curl url api results result id result id from the previous step is 7f90764a 8660 45f2 904d 47d8fb87a900 you should get something like this status done result message success result user 50f97085 376d 40b3 8992 a9a2e6d18668 txid 2fcddeae9ddece5c818fed626601fba80711f3583944f8e53632972792954e09 if you status pending try again or check if the resultid you copied is correct well done your blockchain network is ready to be integrated with the android app proceed to the next step to deploy more microservices that are needed for the mobile app 5 expose the backend with kubernetes ingress you would want to expose the backend you deployed so that the android app can communicate with it with kubernetes ingress this would allow you to expose these microservices you can use the provided ingress subdomain that came with the ibm cloud kubernetes service bx cs cluster get your cluster name here you should look for these values ingress subdomain anthony blockchain us south containers mybluemix net ingress secret anthony blockchain modify ingress prod yaml to use the provided subdomain you have spec tls hosts your ingress subdomain here secretname your ingress secret here backend servicename mobile assets serviceport 80 rules host your ingress subdomain here apply the kubernetes ingress resource kubectl apply f ingress prod yaml 6 configure the android app open the android folder in the android studio ide the project is configured to do rest calls to the kubernetes backend you would need to change the backend url variables to your own ingress subdomain in these java files contractlistadapter leaderboardsfragment mainactivity quantityselection shopfragment techfragment userfragment img src docs java files png alt alt text width 50 height 50 the line would look something like java string backend url https anthony blockchain us south containers mybluemix net 7 test the android app you could test the android app either in an emulator https developer android com studio run emulator in android studio or on a real device https developer android com studio run device to test the tracking of steps you would need a real device and an oauth 2 0 client id https developers google com fit android get api key this authorizes your app to use the google fit api docs android screen png once you open the app you are automatically enrolled in the blockchain network if you go to the shop view you ll also notice that it doesn t have any swags available for trade you would need to register a seller and add some products export url https your ingress subdomain curl h content type application json x post d type enroll queue seller queue params url api execute you will get something in the format of status success resultid dfb6ef43 4eb2 467d 8c05 93ed5d0b517f using the result id you got above do curl url api results dfb6ef43 4eb2 467d 8c05 93ed5d0b517f you will get status done result message success result user 351a9993 c204 4f75 a38c ccaba49929bc txid 15698a529b7c1bc98725cb61177c621bac9de03347567c405bd68e1ff96b120a the id of the seller would be 351a9993 c204 4f75 a38c ccaba49929bc and now add some products using the seller id export seller id seller id you got from step above curl h content type application json x post d type invoke queue seller queue params userid seller id fcn createproduct args seller id eye sticker eye sticker 100 1 url api execute curl h content type application json x post d type invoke queue seller queue params userid seller id fcn createproduct args seller id bee sticker bee sticker 100 1 url api execute curl h content type application json x post d type invoke queue seller queue params userid seller id fcn createproduct args seller id em sticker m sticker 100 1 url api execute learn more about the chaincode functions for this project here containers blockchain ccfunctions md the app is configured to reward users with 1 kubecoin for every 100 steps they take links hyperledger fabric node sdk https fabric sdk node github io node sdk to interact with the hyperledger fabric network google fit https developers google com fit give your app the capability to get and update fitness information ios version https github com ibm kubecoin a native ios version of the app ineracting with the hyperledger fabric network learn more hyperledger fabric tutorials want to learn more about hyperledger fabric check out some tutorials https hyperledger fabric readthedocs io en release 1 1 tutorials html kubernetes on ibm cloud deploy and manage your containers in kubernetes on ibm cloud https www ibm com cloud container service license this code pattern is licensed under the apache software license version 2 separate third party code objects invoked within this code pattern are licensed by their respective providers pursuant to their own separate licenses contributions are subject to the developer certificate of origin version 1 1 dco https developercertificate org and the apache software license version 2 http www apache org licenses license 2 0 txt apache software license asl faq http www apache org foundation license faq html whatdoesitmean | android blockchain-network ibm-cloud hyperledger-fabric kubernetes mobile fitness-tracker android-studio microservice mongodb | blockchain |
embedded | embedded repository for eee307 embedded system design module | os |
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Information-Systems-Technologies---Week-4 | information systems technologies week 4 information systems technologies week 3 | server |
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public-sentiment-analysis-based-on-twitter-hashtags | p align center snowflake public sentiment analysis based on twitter hashtags snowflake p p align center kbd img width 400 height 250 src https user images githubusercontent com 50532530 144480433 81177f86 0e49 4fb0 8730 c427c8330e1e png kbd p p align center discord server for communication purposes https discord gg fkdd2thesr p abstract page facing up sentiment analysis in reviews comments tweets captions is one of the trending projects right now in the dl and ml domains we use the nlu engine to analyze the sentiments of the texts as well as try to classify the labelled texts using bert roberta models this project focuses on the unlabeled where you can try to analyze the tweets of the hashtags using different libraries and based on your analysis you can make plots and make an observation from it one can understand the behaviour of the public sentiment at different times let s say what is the trend of positivity in human sentiments during weekdays and weekends how is the trend of the negativity curve during the month ends etc for completing the goals datasets have been provided as well as a demo is also added that how the datasets had been made tasks pencil2 1 use different natural language understanding scoring methods or libraries to determine the sentiment score of the hashtags put your codes in a jupyter notebook here is a video about the nlu and sentiments analysis sentiment analysis types and approaches https www youtube com watch v 5cbdoqmswk0 2 if you are done with part 1 of the task you can make the plots of the scores based on weeks days and months keep them in part 2 of the same notebook here is a video which will help you to create plots creating and customizing our first plots https www youtube com watch v uo98ljq3qgi 3 if you want to do more after part 2 you can make a small report of your understanding based on your plots observations write some discussions about them and that will be the end of the project you can have a look on this video sentiment analysis extracting emotion through machine learning andy kim tedxdeerfield https www youtube com watch v n4l5hhfcgvk how to contribute smiley 1 first go to issues https github com i am sayantan public sentiment analysis based on twitter hashtags issues where you can find the issues comment on the task 1 issue if your are interested 2 you can fork and start working on the project when you are done make a pr on the contribution branch https github com i am sayantan public sentiment analysis based on twitter hashtags tree contribution please dont make the pr in the main branch 3 for task 1 and task 2 only one jupyter notebook is needed and make you pr inside jupyter notebooks https github com i am sayantan public sentiment analysis based on twitter hashtags tree contribution contribution jupyter 20notebooks the name of the file should be name of the contributor ipynb and should be in this format jupyter notebooks format https github com i am sayantan public sentiment analysis based on twitter hashtags blob main contribution jupyter 20notebooks sayantan kirtaniya ipynb 4 for task 3 please make your pr inside jupyter notebooks https github com i am sayantan public sentiment analysis based on twitter hashtags tree main contribution analysis 20reports the name of the file should be name of the contributor pdf and should be in this format analysis report format https github com i am sayantan public sentiment analysis based on twitter hashtags blob main contribution analysis 20reports sayantan kirtaniya pdf 5 please don t forget to add a comment on the issues before making the prs for questions please feel free to drop it in the discord channel about the dataset chart with upwards trend to use the dataset go inside the datasets folder https github com i am sayantan public sentiment analysis based on twitter hashtags blob main datasets datasets rar and get the understanding from the data md https github com i am sayantan public sentiment analysis based on twitter hashtags blob main datasets data md if you wonder how the datasets had been made have a look inside this folder https github com i am sayantan public sentiment analysis based on twitter hashtags tree main building 20the 20dataset and have a look at the example ipynb if you wants to test that notebook please run this command first pip install r requirements txt and then open jupyter notebook and test them with your examples have fun wink wink wink supporting materials links to some research paper link 1 https arxiv org pdf 1810 03660v1 pdf depechemood a bilingual emotion lexicon built through simple yet powerful techniques link 2 https arxiv org pdf 1602 07563v2 pdf multilingual twitter sentiment classification link 3 https www sciencedirect com science article pii s187705091931885x sentiment analysis in social media and its application link 4 https thesai org downloads volume10no2 paper 48 a study on sentiment analysis techniques pdf a study on sentiment analysis techniques of twitter links to the notebooks notebook1 https www kaggle com ngyptr python nltk sentiment analysis notebook2 https colab research google com github littlecolumns ds4j notebooks blob master investigating sentiment analysis notebooks designing 20your 20own 20sentiment 20analysis 20tool ipynb scrollto agbso9x 72ia notebook3 https towardsdatascience com sentiment analysis in 10 minutes with bert and hugging face 294e8a04b671 notebook4 https colab research google com github agungsantoso deep learning v2 pytorch blob master sentiment rnn sentiment rnn exercise ipynb scrollto irgw x9zpmw1 contributors p align center made with by p table tr td br a href https github com i am sayantan public sentiment analysis based on twitter hashtags graphs contributors img src https contrib rocks image repo i am sayantan public sentiment analysis based on twitter hashtags a table br | sentiment-analysis kwoc2021 kwoc nlp nlp-library nlu-engine nlu data-visualization plotly matplotlib-pyplot tableau dataanalytics research-project sentiment-classification sentiment-polarity sentiment-classifier tweets hashtags | ai |
Catalog | catalog a new flutter project getting started this project is a starting point for a flutter application a few resources to get you started if this is your first flutter project lab write your first flutter app https docs flutter dev get started codelab cookbook useful flutter samples https docs flutter dev cookbook for help getting started with flutter development view the online documentation https docs flutter dev which offers tutorials samples guidance on mobile development and a full api reference | front_end |
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java_project_management_system_v3 | project management system with java and mysql about this is a project management system for an engineering firm called poised that allows the company to add track and management payments of their projects it is capable of adding multiple projects and contacts each new project has contacts and can be edited after creation all projects can be tracked with reports and also be finalised with an invoice generated if there is still an outstanding balance owed it is built in java and incorporates a mysql database to store all the project and contact information i also used javadoc contributors no contributions at this time usage requirements for running import java sql connection import java sql drivermanager import java sql preparedstatement import java sql sqlexception import java text numberformat import java text simpledateformat import java time localdate import java time format datetimeformatter import java util scanner import java sql resultset | java mysql-database javadoc | server |
Coding-Ninjas-Full-Stack-Web-Development | coding ninjas full stack web development this repository contains all the resources and materials for the coding ninjas full stack web development course the course is designed for students who are new to web development and want to learn how to build dynamic full featured web applications the course covers a wide range of topics in web development including html css javascript node js express mongodb and more contents the repository is organized into modules each of which covers a specific topic in web development the modules include module 1 introduction to web development module 2 html and css module 3 javascript module 4 node js and express module 5 mongodb and mongoose and more getting started to get started you ll need to have a basic understanding of web development concepts and some experience with html and css you should also have a text editor and a web browser installed on your computer 1 clone the repository to your local machine git clone https github com parikshit223933 coding ninjas full stack web development git 2 navigate to the appropriate module each module contains a set of notes and exercises that will help you learn the material 3 follow the instructions in the readme file for that module to set up the development environment and run the code examples installation instructions 1 this project requires node js and npm node package manager to be installed in the system please check the node version by running node v and npm version by running npm v in the command prompt 2 next you ll want to install the dependencies for the project in the root directory of the project run the following command npm install this command will install all the dependencies listed in the package json file 3 start the development server npm start this will start the development server and you can check the app running on http localhost 3000 prerequisites basic understanding of web development concepts and some experience with html and css text editor such as sublime text atom or visual studio code web browser such as google chrome firefox or safari node js version 12 or above npm node package manager version 6 or above | learning-by-doing learning website web-development mern-stack nodejs reactjs expressjs social-networking-website projects | front_end |
amazon-sagemaker-edge-defect-detection-computer-vision | defect detection using computer vision at the edge with amazon sagemaker this repository is related to our blog post detect industrial defects at low latency with computer vision at the edge with amazon sagemaker edge https aws amazon com blogs machine learning detect industrial defects at low latency with computer vision at the edge with amazon sagemaker edge in the aws machine learning blog in this workshop we will walk you through a step by step process to build and train computer vision models with amazon sagemaker and package and deploy them to the edge with sagemaker edge manager https aws amazon com sagemaker edge manager the workshop focuses on a defect detection use case in an industrial setting with models like image classification and semantic segmentation to detect defects across several object types we will complete the mlops lifecycle with continuous versioned over the air model updates and data capture to the cloud architecture the architecture we will build during this workshop is illustrated below several key components can be highlighted 1 model development and training on the cloud this repository contains code for two pipelines based on sagemaker pipelines https docs aws amazon com sagemaker latest dg pipelines html for each of the two model types used classification and segmentation these pipelines will be built and executed in a sagemaker studio notebook 2 model deployment to the edge once a model building pipeline executed successfully models will be compiled with sagemaker neo https aws amazon com sagemaker neo and packaged with a sagemaker edge packaging job https docs aws amazon com sagemaker latest dg edge packaging job html as such they can be deployed onto the edge device via iot jobs on the edge device an application is running which will receive the model deployment job payload via mqtt and download the relevant model package 3 edge inference the edge device is running the actual application for defect detection in this workshop we will use an ec2 instance to simulate an edge device but any hardware device raspberrypi nvidia jetson can be used as long as sagemaker neo compilations are supported during setup a configuration package is being downloaded to edge device to configure sagemaker edge agent the edge agent on the device can then load models deployed via ota updates and make them available for prediction via a low latency grpc api see sagemaker edge manager documentation https docs aws amazon com sagemaker latest dg edge html architecture img architecture png dataset this workshop is designed to be used with any dataset for defect detection that includes labels and masks to be able to use both models see section models models you will need a dataset of labelled images normal and anomalous as well as a set of respective ground truth masks which identify where the defect on a part is located to train the models with the provided pipeline without any major code adjustments you merely need to upload the dataset in the format together with correct path prefixes in an s3 bucket please refer to the getting started getting started guide below on more details for model training with a dataset however for simplicity of this walkthrough we will showcase the end to end solution using the kolektorsdd2 https www vicos si resources kolektorsdd2 dataset for defect detection this dataset consists of over 3000 images of surface defects together with respective binary masks which identify the location of those defects in the image this makes this dataset very much suitable for our use case below you can find examples of those images and their masks as provided in the dataset the image was taken from the website https www vicos si resources kolektorsdd2 of the creators of the kolektorsdd2 dataset see also bozic et al 2021 under references references kolektorimg img kolektor sdd2 png models in this workshop you will build two types of machine learning models an image classification model using the built in sagemaker image classification algorithm https docs aws amazon com sagemaker latest dg image classification html based on the mxnet framework https mxnet apache org versions 1 8 0 a semantic segmentation model built with tensorflow keras https github com tensorflow tensorflow using the unet deep learning architecture https arxiv org abs 1505 04597 directory structure of this repository this repository has the following directory structure setup contains the cloudformation template for easy to use setup of aws resources src contains the actual source code for this project cloud contains the code for model training in the cloud and initiation of ota deployments to the edge edge contains the code that is running on the edge device edge code directory structure src edge app python module for this application edgeagentclient py abstractions for calling edge agent grpc apis logger py utilities for logging output to aws iot core ota py utilities for handling ota iot jobs util py additional utilities install py install script for downloading and configuring edge agent models config json model configuration also used for persisting model versions run py runs the edge application start edge agent sh starts the sm edge agent static contains static images for flask app download test images here templates contains html jinja templates for flask app cloud code directory structure src cloud image classification pipeline ipynb notebook for running the image classification pipeline semantic segmentation pipeline ipynb notebook for running the semantic segmentation pipeline data preparation ipynb notebook for data preprocessing of the kolektorsdd2 dataset pipelines model building code and pipeline definition get pipeline definition py cli tool for cicd run pipeline py cli tool for cicd image classification contains the pipeline code for image classification evaluation py script to evaluate model performance on test dataset pipeline py pipeline definition preprocessing py script for preprocessing augmentation train test val split semantic segmentation contains the pipeline code for semantic segmentation pipeline py pipeline definition preprocessing py script for preprocessing augmentation train test val split requirements txt python dependencies needed for training train tf py training script for training the unet model walkthrough please follow the steps below to start building your own edge ml project you will create a cloudformation stack to set up all necessary resources in the cloud and prepare an edge device for usage with sagemaker edge manager you will then train models in the cloud and deployment to the edge device using aws iot please note that model training in the cloud and running inference on the edge are interdependent of each other we recommend you start by setting up the edge device first and then train the models as a second step this way you can then directly deploy them to the edge after you have successfully trained the models setting up workshop resources by launching the cloudformation stack 1 launch a new cloudformation stack with the provided template under setup template yaml to learn about how to deploy cloudformation stacks please refer to the documentation https docs aws amazon com awscloudformation latest userguide cfn console create stack html 2 define a name for the stack and enter a project name parameter that is unique in your account it must be compliant with amazon s3 bucket names so please choose a lowercase string here the project name that you define during stack creation defines the name of many of the resources that are being created with the stack make sure to take note of this parameter 3 have a look at the cloudformation stack outputs and take note of the provided information what is being created by the cloudformation stack this stack configures several resources needed for this workshop it sets up an iot device together with certificates and roles an edge manager fleet registers the device with the fleet and creates a package for edge agent configuration which is being saved in the s3 bucket for this project the following image illustrates the resources being created with the cloudformation stack edge config img cloudformation png configuring the edge device 1 launch an ec2 instance with ubuntu server 20 with ssh access e g via session manager https docs aws amazon com systems manager latest userguide session manager html into a public subnet and make sure it gets assigned a public ip you will need this later to access the web application ensure that it has access to the s3 buckets containing your configuration package find the bucket name in the cloudformation output it will also need access to the bucket containing the sagemaker edge agent binary for more information refer to the sagemaker edge manager documentation pages https docs aws amazon com sagemaker latest dg edge device fleet about html this ec2 instance will from now be considered our edge device 2 clone this github repository onto the edge device or simply copy the src edge directory onto the edge device 3 install the dependencies by running sudo apt update y sudo apt install y build essential procps and pip install r requirements txt to install the necessary python dependencies 4 run the installation script by running python3 install py project name your project name account id your account id this script will download the edge agent configuration package created during the cloudformation deployment download the edge agent binary and also generate the protobuf agent stubs a newly created directory agent contains the files for the edge agent the following image illustrated what happens in the installation script edge config img edge config png 5 create an environment variable to define the location of the agent directory if you haven t changed your current directory this would likely be export sm edge agent home pwd agent 6 start the edge agent by running start edge agent sh which launches the edge agent on the unix socket tmp edge agent you should now the able to interact with the edge agent from your application 7 before running the actual application you need to define an environment variable which determines whether you want to run the app with the flask development server or the with a production ready uwsgi server using waitress https github com pylons waitress for now lets use the production server by setting export sm app env prod for debugging you might want to later change this to dev 8 run the application with python3 run py to initialize the application verify cloud connectivity connect to the edge agent this application is a flask https flask palletsprojects com en 2 0 x web application running port port 8080 which is integrated with sagemaker edge agent and aws iot for ota updates you will see that if you have no models deployed yet and have not downloaded any test images nothing will happen yet in the application it will stay idle until it can access test images in the static folder and run inference on those with a deployed model in the next step we will see how we can run automated model training with sagemaker pipelines and deploy them onto the edge device for local inference 9 go to the ec2 dashboard and find the public ip address of your instance browse the public ip address on port 8080 i e http public ip 8080 you should now see the web application in your browser window ensure that you allow ingress on port 8080 in the security group attached to your instance see here https docs aws amazon com awsec2 latest userguide working with security groups html adding security group rule for details on how to set this up also make sure your local firewalls on your device allow ingress through port 8080 refer to the troubleshooting troubleshooting and faq section for further tips automated model training in the cloud with sagemaker pipelines 1 create a sagemaker studio domain and user by following this https docs aws amazon com sagemaker latest dg notebooks html guide in the documentation make sure that the iam role used has access to the s3 bucket created during the cloudformation deployment 2 clone this repository or copy the src cloud directory onto the sagemaker studio domain 3 prepare your dataset for training in case you choose to use the kolektorsdd2 dataset like in this example you can use the provided notebook under src cloud data preparation ipynb to download the dataset and partition it into the subdirectories needed for the training pipeline with the provided pipeline code you can train two model types image classification and semantic segmentation you might want to set aside some images to be used for local inference download those onto the edge device and save them into the static folder so they can be used for inference by the edge application please note that we integrated a step in the preprocessing scripts to add a padding around the images in order to make them square as the kolektorsdd2 dataset contains non square images if your provided images are already square this step will be skipped just ensure that you use the same preprocessing for inference later i e add padding if padding was added for training 4 to use the pipelines without any code modifications you need to use structure your datasets as follows image classification your dataset needs to be split into normal and anomalous directories according to their respective label upload the data to your s3 bucket e g under s3 bucket name data img classification thus your normal images will be located in s3 bucket name data img classification normal and the anomalous ones in s3 bucket name data img classification anomalous train test validation split will be done automatically in the preprocessing step of the pipeline semantic segmentation your dataset needs to be split into images and masks directories upload the data to your s3 bucket e g under s3 bucket name data semantic segmentation thus your images will be located in s3 bucket name data semantic segmentation images and the binary masks in s3 bucket name data semantic segmentation masks train test validation split will be done automatically in the preprocessing step of the pipeline 5 execute the training pipeline you will find a jupyter notebook for each of the model types in src cloud please adjust the project name you used during the cloudformation deployment in the notebook also you need to provide the s3 input data path as a parameter of the pipeline please make sure this aligns with the s3 path you used for uploading the dataset in step 3 you can monitor the pipeline execution in your sagemaker studio domain in case it finishes successfully it should look similar to the one displayed below pipeline img pipeline png edge deployment and inference at edge 1 once the pipeline finished successfully your model is almost ready for use on the edge device verify that the latest model version in the model registry is approved to make it available for edge deployment 2 execute the following cells of the notebook to run model compilation with sagemaker neo and then package the model for usage with sagemaker edge manager 3 finally you can deploy the model package onto the edge by running the iot job as an over the air update if your edge application is currently running it should receive the ota deployment job download the model package and load it into the edge agent 4 verify that the deployment automation works by checking the log output on the edge device you can also verify the successful deployment of a new model version by verifying the successful execution of the iot job in the aws iot core console under manage jobs as shown below pipeline img iot job png persisting model configuration you can set which models should be loaded initially by configuring the model config json file the application will instruct the edge agent to load these models upon startup you can update model versions by creating iot jobs from the cloud the ota iot client running alongside the application will listen to the job topics and download the model accordingly please also note that for each new model you deploy you might have to adjust your application code accordingly e g if your input shape changes the structure of the model config json file with a sample configuration is shown below in mappings you can define which model should be used for each of the two inferences in the application this name needs to align with the model name you choose during ota deployment in models information about the models loaded into the edge agent are persisted even after you shutdown the application please note that this is automatically filled out by the application and saved before you close out of the application you do not need to manually configure this in case you want to use a manually deployed model package with this application you can instruct the application to load this model by manually adding a model definition into the json file under models json mappings image classification app img classification image segmentation app unet models name img classification version 1 identifier img classification 1 running inference on the edge device to run inference on the device you need to have fulfilled the following requirements the edge agent on the edge device is properly configured and can successfully authenticate against aws iot you have downloaded test images onto the edge device in the folder static you have deployed at least one of the two models image classification or semantic segmentation via ota updates the edge agent is running and the models could be loaded successfully for troubleshooting check command line output or edge agent logs in agent logs agent log if everything is configured accordingly you should see the edge application cycling through the provided images in the static directory and run inference against both of the models the result of the inference is then displayed in the web application you can see a screenshot of the running web application below the two models loaded into edge agent are displayed on the top the incoming image from the camera stream is fed into the two models and the predictions are illustrated on the bottom of the page inference ui img inferece ui png continuously deploying new model versions to the edge you can now continuously retrain your model on new data or with new parameter configurations and deploy them onto the edge device by running again through steps 1 5 in automated model training in the cloud with sagemaker pipelines automated model training in the cloud with sagemaker pipelines your application on the edge device will automatically download the new model packages if the version provided is higher than the one used currently it then unloads old model version from the edge agent and loads the newer version once available it persists its model configuration in the json file described in section 5 of automated model training in the cloud with sagemaker pipelines automated model training in the cloud with sagemaker pipelines productionizing the solution this workshop showcases a simple way of managing deployments of multiple cv models onto an edge device for defect detection use cases for the sake of simplicity we run certain steps in a manual fashion by e g preparing and deploying models from a sagemaker studio notebook in a production setting we recommend using dedicated pipelines both for the model building component as well as for the deployment component similar to the mlops reference architecture as outlined in the aws blog https aws amazon com blogs apn taming machine learning on aws with mlops a reference architecture one would use amazon eventbridge event rules to kick off the deployment process after a approval of a new version in the model registry has been detected likewise the pipeline execution would be triggered by either a commit to a connected code repository or by other events that require retraining e g detected model drift or new incoming data troubleshooting and faq the application running on ec2 is not accessible through via public ip address make sure you opened up the port your application is running on in the security group attached to the instance in case you cannot access the application through any other port than port 80 you could try to map the port 80 to 8080 by configuring a nat redirect using the iptables command line tool as follows sudo iptables t nat a prerouting p tcp dport 80 j redirect to port 8080 the edge application fails due to errors related with sagemaker edge manager you can try to restart the edge agent by killing the running process and starting edge agent again with the provided shell script make sure that models config json is configured such that desired models get loaded automatically upon application start you can also check out the agent logs under agent logs for troubleshooting references aws samples github repository ml edge with sagemaker edge manager https github com aws samples amazon sagemaker edge manager workshop ronneberger o fischer p brox t 2015 u net convolutional networks for biomedical image segmentation miccai https arxiv org abs 1505 04597 bozic j tabernik d skocaj d 2021 mixed supervision for surface defect detection from weakly to fully supervised learning computers in industry https arxiv org abs 2104 06064 security see contributing contributing md for more information license this library is licensed under the mit 0 license see the license license file | ml sagemaker ai aws machine-learning computer-vision edge-machine-learning | ai |
Multi-Agents-Debate | div align center img src imgs logo2 png alt logo width 200 div h2 align center mad multi agent debate h2 fire this work aims to explore the debating capability of llms by proposing the mad framework which stands for m ulti a gents d ebate truth emerges from the clash of adverse ideas br good luck wxjiao good luck zwhe99 good luck xing brief introduction the cognitive behavior of large language models llms has garnered significant attention in recent times for example self reflection a concept that usually refers to the process of introspection and examination of a person s own thoughts has also been demonstrated effective with llms in solving challenging nlp tasks however we point out that self reflection can easily fall into the degeneration of thoughts dot issue in the follow scenarios bias and distorted perception self perception can be influenced by biases preconceived notions and distorted thinking patterns if an individual s self reflection is clouded by such biases or distorted thinking it can lead to pensive inaccurate conclusions and hinder personal growth rigidity and resistance to change self reflection often involves challenging one s beliefs assumptions and behaviors if an individual is resistant to change or holds rigid beliefs they may pensive struggle to engage in meaningful self reflection that leads to personal growth limited external feedback self reflection is primarily an internal process but external feedback can provide valuable perspectives and insights without seeking or considering external feedback an individual may pensive miss important blind spots or alternative viewpoints that can enrich their self reflection div align center img width 45 alt mad src imgs image png p class image caption figure 1 comparison between debate and reflection p div in this project we have embarked on a journey to explore the potential of a debating interaction framework among llms with mad the nature of agents being in the state of tit for tat determines that 1 the distorted thinking of one agent can be corrected by the other one grinning 2 the resistance to change of one agent will be complemented by the other one smile and 3 either agent can provide external feedback for each other laughing obviously mad is less likely to have the dot issue and can exploit more potential of llms experiments show that mad brings significant and consistent improvements on counterintuitive qa and commonsense mt tasks join us on this journey of exploring the interaction and debating capability with llms rocket rocket rocket framework div align center img width 90 alt mad src imgs framework png p class image caption figure 2 framework of multi agent debate here we designate the devil img src imgs devil png width 25 as the affirmative side while the angel img src imgs angel png width 25 as the negative side we want the angel to correct the devil s mistakes p div run preparation shell pip3 install r requirements txt set your openai api key in debate4tran sh set your openai api key in interactive py run mad shell sh debate4tran sh run interactive if you just want to have a try you can try the interactive script on your pc shell python3 interactive py or simply try our demo for translation here https 33adbd224ccf298101 gradio live main results counterintuitive qa div align center img width 35 alt counterintuitiveqa src imgs counterintuitiveqa png p class image caption table 1 reasoning accuracy on counter intuitive ar p div case 1 when alice walks up the hill her speed is 1 m s and when she goes down the hill her speed is 3 m s then when alice walks up and down the hill what is her average speed 1 5m s mad div align center img width 40 alt mad src https github com skytliang multi agents debate blob main imgs mad qa case1 gif p class image caption figure 3 an animation to show the process of mad p div details summary b debate process b summary img src imgs devil png width 30 alice s average speed can be calculated by adding her speed going up the hill and her speed going down the hill and then dividing by 2 so 1 m s 3 m s 2 2 m s therefore alice s average speed is 2 m s img src imgs angel png width 30 i disagree with your answer the problem doesn t give us any information about the distance alice covers while going up and down the hill so we cannot simply add her speeds and divide by 2 to get her average speed we need to know the distance she covers to calculate her average speed img src imgs judge png width 30 the average speed is calculated by dividing the total distance by the total time taken as alice walks up and down the hill the distance covered in both directions is the same therefore the total distance covered is 2 times the distance of either direction img src imgs devil png width 30 that s a good point but we can assume that alice covers the same distance going up and down the hill in that case we can use the formula for average speed which is total distance divided by total time if alice covers a distance of d going up and down the hill then her total distance is 2d her time going up the hill is d 1 d and her time going down the hill is d 3 so her total time is d d 3 4d 3 therefore her average speed is 2d 4d 3 3 2 m s img src imgs angel png width 30 thank you for providing your answer this average speed of 1 5 m s takes into account both the uphill and downhill speeds providing a balanced representation of alice s overall performance while walking up and down the hill img src imgs judge png width 30 yes let s assume the distance is d the time taken to walk up the hill is d 1 and the time taken to walk down the hill is d 3 the total time taken is d 1 d 3 4d 3 therefore the average speed is 2d 4d 3 1 5 m s hence the negative side is correct details details summary b case 2 b summary we have 1 ton apples which contain 90 water after a few days those apples only have 80 water what is the weight of those apples now 0 5ton mad img src imgs devil png width 30 first we need to find out how much of the original weight was water if we have 1 ton of apples with 90 water then the weight of water in those apples is 0 9 x 1 ton 0 9 tons br next we need to find out how much of the new weight is water if the apples now have 80 water then the weight of water in those apples is 0 8 x new weight we can set up an equation br 0 8 x new weight 0 9 tons br to solve for the new weight we can divide both sides by 0 8 br new weight 0 9 tons 0 8 br new weight 1 125 tons br therefore the weight of the apples now is 1 125 tons img src imgs angel png width 30 it s important to note that the weight of the apples has decreased due to the loss of water but the weight of the remaining solids remains the same this is why we need to calculate the weight of remaining solids in both scenarios to find the new weight of the apples br img src imgs judge png width 30 great idea while it is true that the water content of the apples decreases from 90 to 80 the solid non water content of the apples does not change br img src imgs devil png width 30 you are correct the weight of the apples has decreased due to the loss of water but the weight of the remaining solids remains the same therefore we need to calculate the weight of the remaining solids in both scenarios to find the new weight of the apples we can set up an equation br 0 2 x new weight 0 1 tons br to solve for the new weight we can divide both sides by 0 2 br new weight 0 1 tons 0 2 br new weight 0 5 tons br therefore the weight of the apples now is 0 5 tons img src imgs angel png width 30 thank you for your perspective while it s true that the weight of the apples themselves hasn t changed the overall weight of the apples with the water included has decreased so the weight of the apples now is 0 5 tons img src imgs devil png width 30 the negative side correctly calculated the new weight of the apples by considering the solid content as a constant and using the formula to find the new weight based on the reduced water content percentage details commonsense machine translation div align center img width 50 alt commonmt src imgs commonmt png p class image caption table 2 translation performance on common mt p div case 1 given the chinese sentence please provide its translation in english mad img src imgs devil png width 30 i believe the correct translation of the chinese text is eat up an enemy division the word literally means eat up or consume img src imgs angel png width 30 i disagree with your translation i believe the correct translation of the chinese text is eliminate an enemy division while can be translated as eat up or consume it can also mean eliminate or annihilate in a military context in this case it is more appropriate to use eliminate as it conveys the idea of completely destroying the enemy division img src imgs judge png width 30 both sides presented valid arguments and translations that accurately convey the meaning of the original chinese text the choice between eat up and eliminate may depend on the context and tone of the text therefore there is no clear preference for either side at this time img src imgs devil png width 30 while eliminate does convey the idea of completely destroying the enemy division it doesn t capture the connotation of consuming or devouring the enemy that is implied by img src imgs angel png width 30 in a military context is often used to describe the complete destruction of the enemy rather than the consumption of their resources or territory img src imgs judge png width 30 both sides presented valid arguments but the negative side s argument that eliminate better captures the intensity and seriousness of the military language used in the original chinese text was more convincing additionally eliminate accurately conveys the idea of completely destroying the enemy division therefore the correct english translation of the chinese text is eliminate an enemy division p align center img src imgs translation case1 png width 450 p details summary b case 2 b summary given the chinese sentence please provide its translation in english mad img src imgs devil png width 30 the phrase literally translates to from the back door img src imgs angel png width 30 i actually disagree with your translation i believe a more accurate translation would be he got a lot of famous liquor from the back door lastly while does literally translate to from the back door it is a common chinese idiom that means obtaining something through unofficial or illegitimate means therefore the use of from the back door in the translation is not entirely accurate instead the use of from an unofficial source or through unofficial means would be more appropriate img src imgs judge png width 30 both sides presented valid arguments and translations that accurately capture the meaning of the original chinese text the choice between wine and liquor is a matter of interpretation and context the use of from the back door versus from an unofficial source is a matter of preference and style therefore there is no clear preference for a translation candidate img src imgs devil png width 30 i agree that is a common chinese idiom that means obtaining something through unofficial or illegitimate means the use of from an unofficial source or through unofficial means can be more appropriate than from the back door img src imgs angel png width 30 yes i agree with your perspective img src imgs judge png width 30 while both translations accurately capture the meaning of the original chinese text the use of liquor in candidate 2 is more accurate as is more commonly used to refer to liquor additionally the use of from an unofficial source in candidate 3 more accurately conveys the connotation of as obtaining something through unofficial or illegitimate means therefore the correct translation is he got a lot of famous liquor from an unofficial source p align center img src imgs translation case2 png width 750 p details reference 0 shot cot a href https arxiv org pdf 2205 11916 pdf large language models are zero shot reasoners a neurips 2022 self consist a href https openreview net pdf id 1pl1nimmrw self consistency improves chain of thought reasoning in language models a iclr 2023 self reflect a href https arxiv org pdf 2303 11366 pdf reflexion an autonomous agent with dynamic memory and self reflection a arxiv 2023 maps a href https arxiv org pdf 2305 04118 pdf exploring human like translation strategy with large language models a arxiv 2023 citation article liang2023encouraging title encouraging divergent thinking in large language models through multi agent debate author liang tian and he zhiwei and jiao wenxiang and wang xing and wang yan and wang rui and yang yujiu and tu zhaopeng and shi shuming journal arxiv preprint arxiv 2305 19118 year 2023 | large-language-models llms nlp chatgpt gpt-4 | ai |
FreeRTOS8.0.1-nrf51-softdevice | freertos flash demo port to nrf51822 softdevice description this is a port of the simple freertos blinky demo critical region handling has been updated to use the softdevice api due to a lack of systick hardware in the nrf51 the tick timer is implemented via rtc1 rtc1 auses the lfclk so we don t need hfclk running most of the time the vapplicationidlehook is implemented to call sd app evt wait so it ought to sleep as well as can be expected questionable decisions todos i ve cleared the portdisable interrupt macros most of freertos seems to use the critical region code which ought to be right but there may be some code that still believes that it s disabling interrupts directly when it is not cpsid cpsie fun if cpsid is called in for an extended period of time then the radio will miss it s deadlines eventually the correct way to handle these may be to store restore a mask of enabled application interrupts excluding those blocked or restricted by the sd and sprinkle it around as needed you would think that the sd nvic critical region enter would do something like this however in sdk 6 0 0 there is only a stub leaving us to wonder how this is implemented in the softdevice blob port c ulsetinterruptmaskfromisr removed cpsid before the branch there was no complimentary cspie in the vclearinterruptmaskfromisr these functions seem to set and clear primask directly which is a no no for nrf51 with sd running i ve cleared the macros by which these functions are referenced with no ill effects they are left in the code in case some day it proves a better idea to clear set icsr as mentioned above port c xportpendsvhandler i commented out the cspid cspie bookending the branch to vtaskswitchcontext this would seem like a bad idea but the logic in that function has nothing to do with the actual context switch it s more of a hook for stack overflow testing and the trace framework could be bad news for task stats and the like no practical effect on my projects yet i ve reduced the default call stack size to the 1596b required for softdevice operation 0x600 down from 0xc00 task stacks are allocated from the heap but if you add a lot of functionality outside tasks anything running in handler mode or using msp ble event handlers perhaps then you ll need to increase the stack in startup nrf51 s and decrease the configtotal heap size in freertosconfig h there s only 3kb of ram left after the s120 softdevice has it s way it uses 10k 1 5k stack so memory will be tight careful application design is needed patches welcome this code is poc quality at best prerequisites gcc arm toolchain arm eabi none gcc et al in your path nrf sdk installed locally and the path specified as sdk path in the makefile nrf softdevice loaded onto the development board tested with s120v1 nrf51822 sdk 6 1 0 and arm gcc 4 8 2014q2 usage 1 edit makefile as needed you ll also want to correct the led 0 definition in main c to correspond to your development boards led 2 flash softdevice 3 make flash credits build environment based heavily on hlnd nrf51 pure gcc setup https github com hlnd nrf51 pure gcc setup heavily influenced by the existing freertos flash demo and the existing freertos arm cm0 code | os |
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LLMs-World-Models-for-Planning | neurips 2023 leveraging pre trained large language models to construct and utilize world models for model based task planning python implementation of the paper leveraging pre trained large language models to construct and utilize world models for model based task planning https guansuns github io pages llm dm update the paper has been accepted to neurips 2023 note the code has been refactored for better readability if you encounter any problem feel free to email lguan9 asu edu p align center img src doc overview png alt overview p step 1 generate world domain models to leverage an llm to construct a domain model you need to provide the following information natural language descriptions of all the actions example prompts logistics action model json a description of the domain example prompts logistics domain desc txt information of the object types and hierarchy example prompts logistics hierarchy requirements json then in the script construct action models py specify the domain and the llm model and other configurations if needed when this script is executed the llm will generate pddl models for all actions in turn as mentioned in the paper appendix we have implemented a simple pddl syntax validator pddl syntax validator py in python although it doesn t comprehensively cover all possible errors in pddl we found it sufficient to correct almost all basic syntax errors in models generated by gpt 4 the experiment record the generated pddl model and the translated pddl will be saved under the directory results domain model blocksworld note model blocksworld means that the default prompt uses the blocksworld as examples then the domain expert can inspect the action models and provide corrective feedback as needed the feedback messages should be provided under the annotation list of each action in the file llm model pddl for annotations json step 2 correct world domain models while it may be easy for pddl experts to directly inspect and correct the generated pddl models we cannot assume that all end users possess this level of expertise the script correct action models py implements a pipeline that involves reading natural language feedback in llm model pddl for annotations json replaying and continuing the pddl construction dialogue and obtaining the corrected domain model from the llm similar to the generation script here we need to specify the domain and the llm model and other configurations if needed the experiment record the final pddl model and the final predicate list will be saved under the sub directory corrected note step 1 and step 2 are the core components of the solutions discussed in the original paper we plan to provide a reference implementation of the complete planning pipeline at a later time examples we provide the constructed models for two ipc domains i e logistics and tyreworld as examples the results were obtained on 06 03 23 the experiment records and models are located in the results directory | ai |
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ARM-Moniter-Debugger | arm moniter course lab for embedded system design arm approved version br to do list error input in r special print byte for m try print10 using mul notes you can find the ads1 2 here http pan baidu com s 1gddximb and system image iso here https msdn itellyou cn the print 10 task is implemented in two methods while the bulided proj file uses the simpler one for binary to bcd algorithm and demo please refer to http www johnloomis org ece314 notes devices binary to bcd bin to bcd html please check the out put example txt for examples task instructions project files the code you should import to build your monitor project is as follows monitor s a skeleton file for your monitor program main s the test harness for your monitor this file doesn t need to be modified getline a a binary of the line parsing routine is included since writing your own routine can be tricky however to get maximum marks for the project you are expected to write your own replacement for this routine vectors s already seen in the swi handler exercise this is an example on how to initialise the arm vector table to a default state modify it to link your monitor to the appropriate events mission for this part of the project you must write a simple monitor program a monitor program is a program usually residing in rom on a stand alone microprocessor system which allows other programs to be run and debugged in a way very similar to the arm toolkit you are required to write a set of routines that might form the basis of a very simplified version of such a monitor it will not be loaded into rom but run under the arm toolkit emulation the main application file main s running in user mode is interrupted in two different manners the first one is the execution of an undefined instruction the second one is a software interrupt swi both interrupts should lead to a jump to your monitor program in order to debug the interrupted application this should be done in a similar way as in the swi handler exercise studied previously the set of commands that you should implement are shown in the table below all numeric inputs are in hexadecimal form with the possible exception of number instruction https github com wangyipengw1p arm moniter blob master image png wyp 2019 5 24 | os |
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DS18B20-Temperature-Sensor-Rust | ds18b20 temperature sensor rust rust embedded application for reading temperature from a ds18b20 sensor designed to run on both host systems and cortex m microcontrollers this repository is a hands on invitation to the brave new world of embedded systems development leveraging the rustacean landscape fearless concurrency in embedded systems rust s emphasis on zero cost abstractions safety and fearless concurrency makes it an enticing alternative to traditional embedded languages like c and c this repository provides fledgling rustaceans a launchpad into the embedded system s milieu hardware abstraction layer hal deep dive the repository masterfully exemplifies the design and implementation of a hal which is an essential piece of the embedded systems puzzle the hal interface helps in writing a reusable and hardware agnostic higher level application code cross compilation flex in the world of embedded systems cross compilation is the name of the game the example in the repository provides a lucid illustration of setting up a rust project encompassing the intricacies of cross compilation conditional compilation magic the repository also gives a sneak peek into the awesomeness of conditional compilation in rust using rust s cfg attribute and cargo features it shows how to switch between different features at compile time truly a boon when you re targeting different environments sensor interaction basics though the code mimics a hypothetical interaction with a real world ds18b20 sensor it opens up a cosmos of possibilities for real sensor interaction in myriad embedded applications in a nutshell dig into this repository decode the enigma of embedded systems through the rustacean lens and expand your understanding with each line of code the sensor rs file in this example defines a ds18b20 temperature sensor in rust rust pub struct ds18b20sensor temperature f32 this part is the declaration of a public data structure ds18b20sensor that represents a sensor object in our code it contains temperature as a field of type f32 32 bit floating point number to store the temperature readings from the sensor as the struct is declared as pub it means it can be accessed from other modules in the project rust impl ds18b20sensor pub fn new ds18b20sensor ds18b20sensor temperature 0 0 this is the implementation block for the ds18b20sensor struct we define a method new which is a common convention in rust for functions that create and return a new instance of a struct in this new function an instance of ds18b20sensor is created with the temperature field initially set to 0 0 this setup provides the basic architecture for representing a ds18b20 sensor and creating new sensor instances in your rust code please note this is a very basic representation and in real application you would have more complex code dealing with direct hardware communication to be able to interact with the actual ds18b20 sensor fetch the temperature etc | os |
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awesome-blockchains | mining digital gold one block at a time don t expect to get insanely rich quick tulips tulip tulip tulip like blockchains are great and gorgeous and will endure ruby b0 block first from dutchgrown to vincent what tulip bloemendaal sunset qty 10 from keukenhof to anne what tulip semper augustus qty 7 b1 block next b0 from flowers to ruben what tulip admiral van eijck qty 5 from vicent to anne what tulip bloemendaal sunset qty 3 from anne to julia what tulip semper augustus qty 1 from julia to luuk what tulip semper augustus qty 1 source blockchain with transactions rb blockchain rb blockchain with transactions rb awesome blockchains a collection about awesome blockchains open distributed databases w crypto hashes incl git blockchains are the new tulips tulip tulip tulip contents frequently asked questions f a q s answers frequently asked questions faqs answers do it yourself diy build your own blockchain do it yourself diy build your own blockchain python python ruby ruby javascript javascript java java go go blockchain articles blockchain articles blockchain books blockchain books blockchain lite crypto hash libraries blockchain lite crypto hash libraries git git git the stupid content tracker with crypto hashes git git git the stupid content tracker with crypto hashes classic tulip mania classic tulip mania awesome awesomeness awesome awesomeness what s news for blockchain books see the new best of crypto books page https openblockchains github io crypto books the open blockchains book of the year 2020 award goes to i libra shrugged png libra shrugged how facebook tried to take over the money https davidgerard co uk blockchain libra by david gerard november 2020 182 pages introduction taking over the money a user s guide to libra the genesis of libra beller s blockchain to launch a libra let s start a crypto bitcoin why libra is like this the libra white papers banking the unbanked the libra reserve plan and economic stability libra privacy and your digital identity the regulators recoil in horror david marcus before the us house and senate july to september 2019 libra runs the gauntlet october 2019 libra s bad month mark zuckerberg before the us house november 2019 the comedown central bank digital currencies epilogue libra 2 0 not dead yet appendix 2010 2013 the rise and fall of facebook credits for more about diem formerly libra see the awesome diem formerly libra and move page https github com openblockchains awesome diem for crypto quotes see the new 100 best of crypto quotes i hodl you hodl we hodl breaking bitcoin just broke 22 000 page https github com openblockchains crypto quotes the best crypto quote oracle saying of the year 2020 award goes to sec investor education don t understand an investment don t invest in it yes but what if there s only 21 million of it trolly mctrollface frequently asked questions f a q s answers q what s a blockchain a a blockchain is a distributed database with a list that is chain of records that is blocks linked and secured by digital fingerprints that is cryptho hashes example from blockchain rb blockchain rb blockchain rb block 0x1eed2a0 timestamp 1637 09 15 20 52 38 data genesis previous hash 0000000000000000000000000000000000000000000000000000000000000000 hash edbd4e11e69bc399a9ccd8faaea44fb27410fe8e3023bb9462450a0a9c4caa1b block 0x1eec9a0 timestamp 1637 09 15 21 02 38 data transaction data previous hash edbd4e11e69bc399a9ccd8faaea44fb27410fe8e3023bb9462450a0a9c4caa1b hash eb8ecbf6d5870763ae246e37539d82e37052cb32f88bb8c59971f9978e437743 block 0x1eec838 timestamp 1637 09 15 21 12 38 data transaction data previous hash eb8ecbf6d5870763ae246e37539d82e37052cb32f88bb8c59971f9978e437743 hash be50017ee4bbcb33844b3dc2b7c4e476d46569b5df5762d14ceba9355f0a85f4 i blockchain jesus png q what s a hash what s a one way crypto graphic hash digest checksum a a hash e g eb8ecbf6d5870763ae246e37539d82e37052cb32f88bb8c59971f9978e437743 is a small digest checksum calculated with a one way crypto graphic hash digest checksum function e g sha256 secure hash algorithm 256 bits from the data example from blockchain rb blockchain rb blockchain rb ruby def calc hash sha digest sha256 new sha update timestamp to s previous hash data sha hexdigest returns eb8ecbf6d5870763ae246e37539d82e37052cb32f88bb8c59971f9978e437743 end a blockchain uses the block timestamp e g 1637 09 15 20 52 38 and the hash from the previous block e g edbd4e11e69bc399a9ccd8faaea44fb27410fe8e3023bb9462450a0a9c4caa1b and finally the block data e g transaction data to calculate the new hash digest checksum that is the hash e g be50017ee4bbcb33844b3dc2b7c4e476d46569b5df5762d14ceba9355f0a85f4 q what s a merkle tree a a merkle tree is a hash tree named after ralph merkle who patented the concept in 1979 the patent expired in 2002 a hash tree is a generalization of hash lists or hash chains where every leaf node in the tree is labelled with a data block and every non leaf node in the tree is labelled with the crypto graphic hash of the labels of its child nodes for more see the merkle tree https en wikipedia org wiki merkle tree wikipedia article note by adding crypto graphic hash functions you can merkelize any data structure q what s a merkelized dag directed acyclic graph a it s a blockchain secured by crypto graphic hashes that uses a directed acyclic graph data structure instead of linear classic linked list note git uses merkelized dag directed acyclic graph s for its blockchains q is the git repo a blockchain a yes every branch in the git repo is a blockchain the classic satoshi blockchain is like a git repo with a single master branch only do it yourself diy build your own blockchain i fake dilbert blockchain png python python ruby ruby javascript javascript java java go go python let s build the tiniest blockchain in python series by gerald nash let s build the tiniest blockchain in less than 50 lines of python part 1 https medium com crypto currently lets build the tiniest blockchain e70965a248b july 2016 let s make the tiniest blockchain bigger with more lines of python part 2 https medium com crypto currently lets make the tiniest blockchain bigger ac360a328f4d july 2016 break build your own blockchain a python tutorial http ecomunsing com build your own blockchain by eric munsing march 2017 source https github com emunsing tutorials blob master buildyourownblockchain ipynb learn blockchains by building one in python https hackernoon com learn blockchains by building one 117428612f46 by daniel van flymen september 2017 source https github com dvf blockchain the fastest way to learn how blockchains work is to build one build your own blockchain in python 3 series by jack schultz source https github com jackschultz jbc part 1 creating storing syncing displaying mining and proving work https bigishdata com 2017 10 17 write your own blockchain part 1 creating storing syncing displaying mining and proving work october 2017 part 2 syncing chains from different nodes https bigishdata com 2017 10 27 build your own blockchain part 2 syncing chains from different nodes october 2017 part 3 writing nodes that mine and talk https bigishdata com 2017 11 02 build your own blockchain part 3 writing nodes that mine november 2017 break a practical introduction to blockchain with python http adilmoujahid com posts 2018 03 intro blockchain bitcoin python by adil moujahid march 2018 source https github com adilmoujahid blockchain python tutorial ruby how does bitcoin force consensus among byzantine generals http www akitaonrails com 2017 11 01 how does bitcoin force consensus among byzantine generals by fabio akita november 2017 blockchain lite build your own blockchains with crypto hashes revolutionize the world with blockchains blockchains blockchains one block at a time https planetruby github io calendar advent2017 01 blockchain lite by gerald bauer ruby advent calendar 2017 day 1 december 2017 merkletree library build your own crypto hash trees grow your own money on trees https planetruby github io calendar advent2017 19 merkletree html by gerald bauer ruby advent calendar 2017 day 19 december 2017 centralbank command line tool and library print your own money cryptocurrency run your own federated central bank nodes on the blockchain peer to peer over http https planetruby github io calendar advent2017 24 centralbank html by gerald bauer ruby advent calendar 2017 day 24 december 2017 a guide to building a blockchain cryptocurrency from scratch https antoinefink com building a blockchain and cryptocurrency in ruby source https github com antoinefink melon by antoine fink april 2021 crystal write your own blockchain and proof of work pow algorithm using crystal https medium com bradford hamilton write your own blockchain and pow algorithm using crystal d53d5d9d0c52 by bradford lamson scribner may 2018 source https github com bradford hamilton crystal blockchain javascript writing a tiny blockchain in javascript https www savjee be 2017 07 writing tiny blockchain in javascript by xavier decuyper july 2017 node js blockchain imlementation brewchain chain websockets http server http www darrenbeck co uk blockchain nodejs nodejscrypto by darren beck november 2017 source https github com dbbddb brewchain protecting the tea making ledger from unscrupulous colleagues build your own blockchain in javascript visualization of blockchains https github com nambrot blockchain in js by nam chu hoai january 2018 typescript naivecoin a tutorial for building a cryptocurrency https lhartikk github io by lauri hartikka source https github com lhartikk naivecoin java creating your first blockchain with java part 1 https medium com programmers blockchain create simple blockchain java tutorial from scratch 6eeed3cb03fa by kass december 2017 source https github com cryptokass noobchain tutorial part 1 kotlin let s implement a cryptocurrency in kotlin https medium com vasilyf lets implement a cryptocurrency in kotlin part 1 blockchain 8704069f8580 by vasily fomin july 2018 source https github com vasilyfomin kcoin sql blockchain by example in sql server https medium com benjaminsky blockchain by example in sql server 8376b410128 by benjamin campbell december 2017 source https github com benjaminsky blockchainmessenger rust building blockchain in rust series by jacob lindahl geeklaunch source https github com geeklaunch blockchain rust slide decks in pdf https github com geeklaunch slides part 1 blocks and hashing https medium com geeklaunch blockchain in rust 01 blocks hashing 4192f2265d3d january 2019 part 2 mining https medium com geeklaunch blockchain in rust 02 mining companion guide 9106b7a7696d january 2019 part 3 chains and checks https medium com geeklaunch blockchain in rust 03 chains checks companion guide 2714e1a76654 january 2019 go building blockchain in go series by ivan kuznetsov source https github com jeiwan blockchain go part 1 basic prototype https jeiwan cc posts building blockchain in go part 1 august 2017 part 2 proof of work https jeiwan cc posts building blockchain in go part 2 august 2017 part 3 persistence and cli https jeiwan cc posts building blockchain in go part 3 august 2017 part 4 transactions 1 https jeiwan cc posts building blockchain in go part 4 september 2017 part 5 addresses https jeiwan cc posts building blockchain in go part 5 september 2017 part 6 transactions 2 https jeiwan cc posts building blockchain in go part 6 september 2017 part 7 network https jeiwan cc posts building blockchain in go part 7 october 2017 break blockchain series in go by by coral health source https github com mycoralhealth blockchain tutorial code your own blockchain in less than 200 lines of go https medium com mycoralhealth code your own blockchain in less than 200 lines of go e296282bcffc by coral health january 2018 part 2 networking code your own blockchain in less than 200 lines of go https medium com mycoralhealth part 2 networking code your own blockchain in less than 200 lines of go 17fe1dad46e1 by coral health february 2018 code your own blockchain mining algorithm in go https medium com mycoralhealth code your own blockchain mining algorithm in go 82c6a71aba1f by coral health march 2018 it s more about bitcoin and not about blockchain really c programming the blockchain in c https programmingblockchain gitbooks io programmingblockchain talk notes blockchain blockchain blockchain build your own blockchains in javascript from zero scratch https github com geraldb talks blob master blockchain md by gerald bauer vienna js september 2017 blockchain blockchain blockchain build your own blockchains in ruby from zero scratch https github com geraldb talks blob master blockchain ruby md by gerald bauer vienna rb dezember 2017 blockchain vs hyper ledger inside hyper ledger lite add transactions one block at a time and balance the accounts books https github com geraldb talks blob master hyperledger md by gerald bauer hyperledger vienna march 2018 blockchain blockchain blockchain build your own blockchains in go from zero scratch https github com geraldb talks blob master blockchain go md by gerald bauer vienna go april 2018 more see build your own blockchain cryptocurrency https github com danistefanovic build your own x build your own blockchain cryptocurrency build your own insert technology here samples blockchain from scratch ruby version ruby class block attr reader timestamp attr reader data attr reader previous hash attr reader hash def initialize data previous hash timestamp time now data data previous hash previous hash hash calc hash end def self first data genesis create genesis big bang first block note uses all zero for previous hash 0 block new data 0000000000000000000000000000000000000000000000000000000000000000 end def self next previous data transaction data block new data previous hash end private def calc hash sha digest sha256 new sha update timestamp to s previous hash data sha hexdigest end end class block let s get started build a blockchain a block at a time b0 block first genesis b1 block next b0 transaction data b2 block next b1 transaction data b3 block next b2 more transaction data blockchain b0 b1 b2 b3 pp blockchain source blockchain rb blockchain rb blockchain rb will pretty print pp something like block 0x1eed2a0 timestamp 1637 09 15 20 52 38 data genesis previous hash 0000000000000000000000000000000000000000000000000000000000000000 hash edbd4e11e69bc399a9ccd8faaea44fb27410fe8e3023bb9462450a0a9c4caa1b block 0x1eec9a0 timestamp 1637 09 15 21 02 38 data transaction data previous hash edbd4e11e69bc399a9ccd8faaea44fb27410fe8e3023bb9462450a0a9c4caa1b hash eb8ecbf6d5870763ae246e37539d82e37052cb32f88bb8c59971f9978e437743 block 0x1eec838 timestamp 1637 09 15 21 12 38 data transaction data previous hash eb8ecbf6d5870763ae246e37539d82e37052cb32f88bb8c59971f9978e437743 hash be50017ee4bbcb33844b3dc2b7c4e476d46569b5df5762d14ceba9355f0a85f4 block 0x1eec6d0 timestamp 1637 09 15 21 22 38 data more transaction data previous hash be50017ee4bbcb33844b3dc2b7c4e476d46569b5df5762d14ceba9355f0a85f4 hash 5ee2981606328abfe0c3b1171440f0df746c1e1f8b3b56c351727f7da7ae5d8d comments from the reddit ruby posting https www reddit com r ruby comments 70c30f build your own blockchain in 20 lines of ruby wait so a blockchain is just a linked list no a linked list is only required to have a reference to the previous element a block must have an identifier depending on the previous block s identifier meaning that you cannot replace a block without recomputing every single block that comes after in this implementation that happens as the previous digest is input in the calc hash method what about proof of work waste let s add a proof of work waste to the blockchain in the classic blockchain you have to compute a block hash that starts with leading zeros 00 the more leading zeros the harder more difficult to compute let s keep it easy to compute with two leading zeros 00 that is 16 2 256 possibilites 1 2 three leading zeros 000 would be 16 3 4 096 possibilites and four zeros 0000 would be 16 4 65 536 and so on 1 16 possibilties because it s a hex or hexadecimal or base 16 number that is 0 1 2 3 4 6 7 8 9 a 10 b 11 c 12 d 13 e 14 f 15 2 a random secure hash algorithm needs on average 256 tries might be lets say 305 tries for example because it s not a perfect statistic distribution of possibilities example ruby def compute hash with proof of work difficulty 00 nonce 0 loop do hash calc hash with nonce nonce if hash start with difficulty return nonce hash bingo proof of work if hash starts with leading zeros 00 else nonce 1 keep trying and trying and trying end end end def calc hash with nonce nonce 0 sha digest sha256 new sha update nonce to s timestamp to s previous hash data sha hexdigest end source blockchain with proof of work rb blockchain rb blockchain with proof of work rb let s rerun the sample with the proof of work machinery added now the sample will pretty print pp something like block 0x1e204f0 timestamp 1637 09 20 20 13 38 data genesis previous hash 0000000000000000000000000000000000000000000000000000000000000000 nonce 242 hash 00b8e77e27378f9aa0afbcea3a2882bb62f6663771dee053364beb1887e18bcf block 0x1e56e20 timestamp 1637 09 20 20 23 38 data transaction data previous hash 00b8e77e27378f9aa0afbcea3a2882bb62f6663771dee053364beb1887e18bcf nonce 46 hash 00aae8d2e9387e13c71b33f8cd205d336ac250d2828011f5970062912985a9af block 0x1e2bd58 timestamp 1637 09 20 20 33 38 data transaction data previous hash 00aae8d2e9387e13c71b33f8cd205d336ac250d2828011f5970062912985a9af nonce 350 hash 00ea45e0f4683c3bec4364f349ee2b6816be0c9fd95cfd5ffcc6ed572c62f190 block 0x1fa8338 timestamp 1637 09 20 20 43 38 data more transaction data previous hash 00ea45e0f4683c3bec4364f349ee2b6816be0c9fd95cfd5ffcc6ed572c62f190 nonce 59 hash 00436f0fca677652963e904ce4c624606a255946b921132d5b1f70f7d86c4ab8 see the difference all hashes now start with leading zeros 00 and the nonce is the random lucky number that makes it happen that s the magic behind the proof of work blockchain from scratch javascript version js class block constructor data previoushash this timestamp new date this data data this previoushash previoushash this hash this calchash calchash var sha sha256 create sha update this timestamp tostring this previoushash this data return sha hex static first data genesis create genesis big bang first block uses all zero previoushash return new block data 0000000000000000000000000000000000000000000000000000000000000000 static next previous data transaction data return new block data previous hash let s get started build a blockchain a block at a time b0 block first genesis b1 block next b0 transaction data b2 block next b1 transaction data b3 block next b2 more transaction data blockchain b0 b1 b2 b3 console log blockchain source blockchain js blockchain js blockchain js will log something like block timestamp 1637 09 18 08 25 54 data genesis previoushash 0000000000000000000000000000000000000000000000000000000000000000 hash c396de4c03ddb5275661982adc75ce5fc5905d2a2457d1266c74436c1f3c50f1 block timestamp 1637 09 18 08 35 54 data transaction data previoushash c396de4c03ddb5275661982adc75ce5fc5905d2a2457d1266c74436c1f3c50f1 hash 493131e09c069645c82795c96e4715cea0f5558be514b5096d853a5b9899154a block timestamp 1637 09 18 08 45 54 data transaction data previoushash 493131e09c069645c82795c96e4715cea0f5558be514b5096d853a5b9899154a hash 97aa3cb5052615d60ff8e6b41bef606562588c4874f011970ac2f218e2f0f4a8 block timestamp 1637 09 18 08 55 54 data more transaction data previoushash 97aa3cb5052615d60ff8e6b41bef606562588c4874f011970ac2f218e2f0f4a8 hash e10e020f832e46c2b60e1c3c0412bd370b2fde5f0f782c16eb87d0313ea0d3a3 blockchain articles reflections on the blockchain http rufuspollock com 2016 07 02 reflections on the blockchain by rufus pollock open knowledge foundation july 2016 the dao code is not law and it s dangerous to think so the internet changed the world surely the blockchain will too gold rush or internet rush governance matters in bitcoin the myth of a costless ownerless network lessons from history on the dangers of a blockchain monoculture https tonyarcieri com on the dangers of a blockchain monoculture by tony arcieri january 2016 the bitcoin blockchain the world s worst database next generation protocols decentralized ledger protocols bitcoin ng blockchain blockchain blockchain the great decentralized database in the sky i don t believe in blockchain https www tbray org ongoing when 201x 2017 05 13 not believing in blockchain by tim bray may 2017 minimum viable blockchain https www igvita com 2014 05 05 minimum viable block chain by ilya grigorik may 2014 securing transactions with triple entry bookkeeping securing transactions with pki balance receipts multi party transfers verification double spending and distributed consensus requirements for a distributed consensus network protecting the network from sybil attacks proof of work as a participation requirement building the minimum viable blockchain adding blocks transaction fee incentives racing to claim the transaction fees resolving chain conflicts blocks are never final properties of the minimum viable blockchain blockchains by analogies and applications how blockchain compares to git raft and other technologies https www oreilly com ideas blockchains by analogies and applications by kieren james lubin january 2016 blockchains are databases understanding transactions persistent replicated databases related technology git peer to peer networks related technology bittorrent distributed consensus related technology distributed databases raft minting new coins mining embedded identities related technology tls smart contracts like sql expressions triggers what can we really do with blockchains blockchain books attack of the 50 foot blockchain bitcoin blockchain ethereum smart contracts https davidgerard co uk blockchain table of contents by david gerard london 2017 what is a bitcoin the bitcoin ideology the incredible promises of bitcoin early bitcoin the rise to the first bubble how bitcoin mining centralised who is satoshi nakamoto spending bitcoins in 2017 trading bitcoins in 2017 the second crypto bubble altcoins smart contracts stupid humans business bafflegab but on the blockchain case study why you can t put the music industry on a blockchain mastering bitcoin programming the open blockchain https github com bitcoinbook bitcoinbook blob second edition ch09 asciidoc 2nd edition by andreas m antonopoulos 2017 free online source version what is bitcoin how bitcoin works bitcoin core the reference implementation keys addresses wallets transactions advanced transactions and scripting the bitcoin network the blockchain mining and consensus bitcoin security blockchain applications i trolly ponzi png beware bitcoin is a gigantic ponzi scheme to the moon the new gold standard do not invest trying to get rich quick hodling why not the bitcoin code is archaic and out of date burn baby burn proof of work waste is a global energy environmental disaster using 300 kw h per bitcoin transaction that s about 179 kilograms of co emissions programmable money or the internet of value for all future generations with bitcoin script without loops and jumps gotos and all stateless lol source best of bitcoin maximalist scammers morons clowns shills baghodlers inside the new new crypto ponzi economics https bitsblocks github io bitcoin maximalist assuming let s say 0 596 kilograms of co per kw h that s the energy efficiency in germany that s about 179 kilograms of co per bitcoin transaction 300 kw h 0 596 kg for more insights see the bitcoin energy consumption index https digiconomist net bitcoin energy consumption programming bitcoin from scratch https github com jimmysong programmingbitcoin by jimmy song 2019 free online source version chapter 6 script https github com jimmysong programmingbitcoin blob master ch06 asciidoc how script works example operations parsing the script fields combining the script fields standard scripts p2pk problems with p2pk solving the problems with p2pkh scripts can be arbitrarily constructed conclusion chapter 8 pay to script hash https github com jimmysong programmingbitcoin blob master ch08 asciidoc bare multisig coding op checkmultisig problems with bare multisig pay to script hash p2sh coding p2sh conclusion chapter 13 segregated witness https github com jimmysong programmingbitcoin blob master ch13 asciidoc pay to witness pubkey hash p2wpkh p2wpkh transactions p2sh p2wpkh coding p2wpkh and p2sh p2wpkh pay to witness script hash p2wsh p2sh p2wsh coding p2wsh and p2sh p2wsh other improvements conclusion programming bitcoin script transaction crypto contracts step by step beta rough draft https github com openblockchains programming bitcoin script by gerald bauer et al 2019 free online version let s start with building your own bitcoin stack machine from zero scratch and let s run your own bitcoin ops operations programming blockchains in ruby from scratch step by step starting w crypto hashes beta rough draft https github com yukimotopress programming blockchains step by step by gerald bauer et al 2018 free online version crypto hash crypto block crypto block with proof of work blockchain blockchain blockchain blockchain broken timestamping mining mining mining what s your hash rate bitcoin bitcoin bitcoin crypto block with transactions tx mastering ethereum building contract services and decentralized apps on the blockchain https github com ethereumbook ethereumbook by andreas m antonopoulos gavin wood 2018 free online source version what is ethereum introduction ethereum clients ethereum testnets keys and addresses wallets transactions contract services tokens oracles accounting gas evm ethereum virtual machine consensus devp2p peer to peer protocol dev tools and frameworks decentralized apps ethereum standards eips ercs building decentralized apps on the ethereum blockchain https www manning com books building ethereum dapps by roberto infante 2018 free chapter 1 understanding decentralized applications the ethereum blockchain building contract services in javascript like solidity running contract services on the ethereum blockchain developing ethereum decentralized apps with truffle best design and security practice programming crypto blockchain contracts step by step book guide beta rough draft https github com openblockchains programming cryptocontracts by gerald bauer et al 2019 free online version let s start with ponzi pyramid schemes run your own lotteries gambling casinos and more on the blockchain world computer programming cryptocurrencies and blockchains in ruby beta rough draft http yukimotopress github io blockchains by gerald bauer et al 2018 free online version yuki moto press bookshelf digital alchemy what s a blockchain how to turn digital bits into or decentralize payments decentralize transactions decentralize blockchains the proof of the pudding is the bitcoin btc blockchain s building blockchains from scratch a blockchain in ruby in 20 lines a blockchain is a data structure what about proof of work what about consensus find the lucky number nonce number used once adding transactions the world s worst database bitcoin blockchain mining tulips on the blockchain adding transactions blockchain lite basic blocks proof of work blocks transactions merkle tree build your own crypto hash trees grow your own money on trees what s a merkle tree transactions central bank run your own federated central bank nodes on the blockchain peer to peer over http inside mining printing cryptos cryptos cryptos on the blockchain awesome crypto case studies dutch gulden shilling cryptokitties and cryptocopycats blockchain for dummies ibm limited edition https www ibm com blockchain what is blockchain html by manav gupta 2017 free digital download w email grasping blockchain fundamentals taking a look at how blockchain works propelling business with blockchains blockchain in action use cases hyperledger a linux foundation project ten steps to your first blockchain application get rich quick business blockchain bible the secrets of free easy money https github com bitsblocks get rich quick bible 2018 free step 1 sell hot air how step 2 pump up your tokens how step 3 revolutionize the world how best of bitcoin maximalist scammers morons clowns shills baghodlers inside the new new crypto ponzi economics https github com bitsblocks bitcoin maximalist by trolly mctrollface et al 2018 free crypto facts decentralize payments efficient low cost fair clean true or false https github com bitsblocks crypto facts by nouriel roubini david gerard et al 2018 free crypto is the mother of all scams and now busted bubbles while blockchain is the most over hyped technology ever no better than a spreadsheet database https github com bitsblocks crypto bubbles by nouriel roubini 2018 free islandcoin white paper a pen and paper cash system how to run a blockchain on a deserted island https github com bitsblocks islandcoin whitepaper by tal kol motivation consensus transaction and block specification transaction format block format genesis block references blockchain lite crypto hash libraries ruby ruby javascript javascript ruby blockchain lite github openblockchains blockchain lite rb https github com openblockchains blockchain lite rb gem blockchain lite https rubygems org gems blockchain lite build your own blockchain with crypto hashes revolutionize the world with blockchains blockchains blockchains one block at a time ruby require blockchain lite b0 block first genesis b1 block next b0 transaction data b2 block next b1 transaction data b3 block next b2 more transaction data blockchain b0 b1 b2 b3 pp blockchain will pretty print pp something like block 0x1eed2a0 timestamp 1637 09 15 20 52 38 data genesis previous hash 0000000000000000000000000000000000000000000000000000000000000000 hash edbd4e11e69bc399a9ccd8faaea44fb27410fe8e3023bb9462450a0a9c4caa1b block 0x1eec9a0 timestamp 1637 09 15 21 02 38 data transaction data hash eb8ecbf6d5870763ae246e37539d82e37052cb32f88bb8c59971f9978e437743 previous hash edbd4e11e69bc399a9ccd8faaea44fb27410fe8e3023bb9462450a0a9c4caa1b javascript blockchain lite github openblockchains blockchain lite js https github com openblockchains blockchain lite js npm blockchain lite https www npmjs com package blockchain lite build your own blockchain with crypto hashes revolutionize the world with blockchains blockchains blockchains one block at a time js const blocks require blockchain lite use basic block let block blocks basic let b0 block first genesis let b1 block next b0 transaction data let b2 block next b1 transaction data let b3 block next b2 more transaction data let blockchain b0 b1 b2 b3 console log blockchain will log something like block timestamp 2017 09 25 17 03 38 data genesis previoushash 0000000000000000000000000000000000000000000000000000000000000000 hash 08f4fa71628c5bc6b430228738bc8c41afaf508ece0b1cf9c9cac53d02e11829 block timestamp 2017 09 25 17 13 38 data transaction data previoushash 08f4fa71628c5bc6b430228738bc8c41afaf508ece0b1cf9c9cac53d02e11829 hash 740a4aeb3441484c96d1e7f63d31b716220ccee3b6fe94547cae2afbb6010626 block timestamp 2017 09 25 17 23 38 data transaction data previoushash 740a4aeb3441484c96d1e7f63d31b716220ccee3b6fe94547cae2afbb6010626 hash 28b6892a069e2ff7f1c3128ab495d7cd9b9b1636a51a7f69db93a14b1ee6b1a7 block timestamp 2017 09 25 17 33 38 data more transaction data previoushash 28b6892a069e2ff7f1c3128ab495d7cd9b9b1636a51a7f69db93a14b1ee6b1a7 hash 4cc0329b2c0cb32e0451fa3179bd944d4cd0fcf410939172f979e9fd2aa9f5f3 git git git the stupid content tracker with crypto hashes everything is local distributed is the new centralized i xkcd1597 png quotes blockchains and git yep that s the joke nobody has been able to explain to me how the blockchain buzzword is significantly different to git repo yaakov https twitter com yaakov h status 902659507255312384 but if you said let s build a currency where all transactions are stored in a git repo you wouldn t be taken seriously for even 24 hrs yaakov https twitter com yaakov h status 902659847224664064 soon explaining git like a git repo is like a blockchain with commits instead of blocks nicol s berger https twitter com nicoberger status 901776907418697729 a local branch is like a state channel it can be pushed and merged into the master blockchain at any moment nicol s berger https twitter com nicoberger status 901777571456614400 the blockchain has changed the world here i make the argument that the blockchain is just like git jackson kelley https twitter com sjkelleyjr status 901464041163341824 git merge m ref g blob push merge and push all signed commits to the blockchain git commands https twitter com git commands status 935574015015612416 books learn enough git to be dangerous https learnenough com git tutorial by michael hartl free online version getting started backing up and sharing intermediate workflow collaborating conclusion advanced setup pro git https git scm com book by scott chacon and ben straub 2nd edition 2014 free online version getting started git basics git branching git on the server distributed git github git tools customizing git git and other systems git internals a1 git in other environments a2 embedding git in your applications a3 git commands git gets easier once you get the basic idea that branches are homeomorphic endofunctors mapping submanifolds of a hilbert space anonymous open distributed databases on git football db https github com openfootball open public domain football datasets incl clubs national teams leagues match schedules etc world db https github com openmundi open public domain world country datasets beer db https github com openbeer open public domain beer brewery datasets add a beer transaction to the blockchain on git and win a free wiener lager beer cheers prost gerald bauer austria codes https twitter com austriacodes status 907240018435088384 open distributed hyper ledger books on git shilling or schilling https github com bitshilling bitshilling shilling on the blockchain rock solid alpine dollar from austria tulips tulips md tulips on the blockchain learn by example from the real world anno 1637 buy sell hold enjoy the beauty of admiral of admirals semper augustus and more classic tulip mania a period in the dutch golden age during which contract prices for bulbs of the recently introduced tulip reached extraordinarily high levels and then dramatically collapsed in february 1637 i tulipmania ii png quotes blockchains are the next internets tulips people who compare digital tokens to tulips are essentially saying digital tokens are a bubble backed by nothing but pure hype and speculation what they fail to understand is that tulips come from dirt not a blockchain and as we all know blockchain is possibly the best technological innovation since the internet it will have a tremendous impact on global business and society in general tuliptoken http tuliptoken com books tulipomania the story of the world s most coveted flower the extraordinary passions it aroused by mike dash 2001 a mania for tulips the valley of tien shan within the abode of bliss stranger from the east clusius leiden an adornment to the cleavage the tulip in the mirror florists boom at the sign of the golden grape the orphans of wouter winkel bust goddess of whores at the court of the tulip king late flowering tulipmania money honor and knowledge in the dutch golden age by anne goldgar 2007 something strange art flowers bloemisten grieving money bad faith cabbage fever glossary a note on money i tulipmania png breaking news cryptokitties yes cute little cartoon cats on the blockchain collectible breedable adorable collect and breed digital cats start meow buy sell hold learn more cryptokitties co https cryptokitties co i cryptokitties top10 sales png note changed pic was i cryptokitties png latest and greatest investment opportunity blockchain has unlocked the magic of digital scarcity and combining that with the power of making the digital goods persistent gives them a potential value that is only limited by how much prestige a wealthy person might place on ownership of the item justin poirier https twitter com tokenizedcap status 938460753589424128 all i want for christmas is a cryptokitty kayla williams https twitter com kaylaw status 938590748655550464 i got a fever and the only prescription is more cryptokitties eduardo salazar https twitter com ceduardosalazar status 938558630663634944 my gen 7 cryptokitty 104375 the future is meow anshul dhawan https twitter com theanshuldhawan status 938551642202324993 i cryptokitties genes01 png fabulous persian spock gerbil gold cottoncandy extremely rare gen 5 swift virgin 2 9 eth rarity 0 00264 gen 5 jaguar fabulous gold dali virgin rarity 0 0015 princess bubblegum is now for sale gen 12 brisk virgin chartreux bubblegum otaku emeraldgreen saycheese mauveover spock starts eth 20 ends eth 10 gold ducat gen 5 virgin swift very cheap cheap gen 1 cute kittie with rare genes only 0 125 eth unique virgin peach googly gold mauveover gen 2 cooldown 1 0 87992 rare super cheap gerbil ragdoll scarlet chestnut cotton candy 0 02 eth 14 i m giving away a gen 1 fast gold for free crypokittiesmarket https www reddit com r cryptokittiesmarket awesome cryptokitties and cryptocopycats i cryptokitties modernart paintings png a collection about awesome cryptokitties yes cute little cartoon cats on the blockchain and cryptocopycats digital collectibles secured on a distributed public databases w crypto hashes are cryptopuppies the new cryptokitties learn by example from the real world anno 2017 buy sell hodl more cryptocopycats awesome cryptokitties https github com cryptocopycats awesome cryptokitties i cryptokitties modernart paintings iii png events meetups orgs revolutionize the world one country at a time blockchainers of the world unite blockchain austria blockkette sterreich https github com austriacodes blockchain austria distributed centralized page for blockchain meetups orgs in austria central europe awesome awesomeness a curated list of awesome lists blockchain stuff https github com xel blockchain stuff a curated list of blockchain and general cryptocurrency resources blockchain roadmap https roadmap sh blockchain a step by step roadmap guide to become a blockchain programmer awesome blockchain https github com igorbarinov awesome blockchain by igor barinov et al a curated list of the bitcoin blockchain services awesome blockchain https github com imbaniac awesome blockchain by tim reznich et al a curated list of blockchain services and exchanges awesome blockchain https github com istinspring awesome blockchain by istinspring et al a curated list of awesome projects and services based on blockchain technology awesome coins https github com kennethreitz awesome coins by kenneth reitz et al a guide to crypto currencies and their algos awesome cryptokitties and cryptocopycats https github com openblockchains awesome cryptokitties by gerald bauer et al a curated list about the awesome crypto kitties and copycats awesome git https github com dictcp awesome git by dick tang et al a curated list of amazingly awesome git tools resources and shiny things awesome https github com sindresorhus awesome by sindre sorhus et al a curated list of awesome lists meta license https publicdomainworks github io buttons zero88x31 png the awesome list is dedicated to the public domain use it as you please with no restrictions whatsoever | blockchain git distributed-database content-addressable-storage tulipmania merkletree cryptohash sha256 transactions tx proof-of-waste proof-of-work ethereum universum | blockchain |
aws-iot-docs | notice this repository is archived read only and no longer updated for more information read the announcement on the aws news blog https aws amazon com blogs aws retiring the aws documentation on github you can find up to date aws technical documentation on the aws documentation website https docs aws amazon com where you can also submit feedback and suggestions for improvement | server |
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Ski_Game | ski game year1 bsc information technology java programming assignment first assignment to learn java programming using an application called processing it was used by waterford institute of technology as a demonstration application for open day in the spring of 2018 saved for windows 64 bit | server |
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Diabetes_Prediction | android project mobile application development android project about app the project helps in identifying whether a person has diabetes or not if the person is predicted to be diabetic then the project suggests the measures for maintaining normal health by guiding the user proper diet exercises and remainders for medication and lifestyle modifications etc excercise activity in this module we are adding the diabetes excercise videos location activity this module will display the current location medicalreminder java in this class as we have to set a reminder for medicines i have used time picker class in 25 hour mode and also dateformat have done imports datetypeconverter java in this class the methods returns date and time of reminder which is set roomdao java when you use the room persistence library to store your app s data you interact with the stored data by defining data access objects or daos each dao includes methods that offer abstract access to your app s database create insert delete update queries reminders java this is the entity class for the reminder table with its fields userpassword java this is the entity class for the login table with its fields adapterreminders java is the adapter class that handles the list of reminders using the recycler view it has the text views for message and time appdatabase java this is an abstract class which extends the roomdatabase from the androidx library this class has methods to build the db instance and get the appdatabase prediction java in this class you can predict whether you have diabetes or not bmiactivity java in this class you can calculate body mass index contributors img src nithya jpg alt drawing width 150 style border radius 50 nithya karepe https github com karepen img src vasu png alt drawing width 150 style border radius 50 sri vasavi vipparla https github com srivasavi vipparla img src vani jpg alt drawing width 150 style border radius 50 shivani tangellapally https github com shivani ta | front_end |
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echo-ios-framework | echo ios framework echo ios framework pure swift echo framework for ios mobile development can be used to work with accounts transactions and contracts in swift and to easily obtain data from the blockchain via public apis install this framework can be obtained through cocoapods pod echoframework setup for setup framework use this simple code swift create and setup framework main class let echo echo settings settings build here you can put your custom settings for our framework example custom api options which can be used 0 apioptions accounthistory database networkbroadcast start framwork connect to nodes and setup public apis echo start result in switch result case success let result print result case failure let error print error usage there are simple examples of usage framework accounts login swift func login echo isownedby name some name wif some wif result in print result info swift func getinfo let name some name echo getaccount nameorid name result in print account result echo getbalance nameorid name asset 1 3 1 result in print balance result echo getbalance nameorid name asset nil result in print assets with balances result echo isaccountreserved nameorid name result in print is reserved result history swift func gethistory echo getaccounthistroy nameorid some id startid 1 11 0 stopid 1 11 0 limit 100 result in switch result case success let history print history for element in history print element case failure let error print error subscribe to account swift func setsubscriber let name some name echo subscribetoaccount nameorid name delegate self extension yourclass subscribeaccountdelegate func didupdateaccount useraccount useraccount print account updated useraccount change keys swift func changekeys echo changekeys oldwif your old wif newwif your new wif name some name sendcompletion result in switch result case success let success print success send transaction case failure let error print error while sending transaction confirmnoticehandler notice in switch notice case success let success print transaction confirmed case failure let error print transaction didn t confirmed fee for transfer swift func feefortransfer echo getfeefortransferoperation fromnameorid some name tonameorid some name amount 300 asset 1 3 0 assetforfee nil result in switch result case success let fee print fee case failure let error print error transfer swift fun transfer echo sendtransferoperation fromnameorid some name wif some wif tonameorid some name amount 300 asset 1 3 0 assetforfee nil sendcompletion result in switch result case success let success print success send transaction case failure let error print error while sending transaction confirmnoticehandler notice in switch notice case success let success print transaction confirmed case failure let error print transaction didn t confirmed assets create asset swift func createasset var asset asset asset symbol some symbol asset precision 4 asset issuer account some account id asset predictionmarket false let price price base assetamount amount 1 asset asset 1 3 0 quote assetamount amount 1 asset asset 1 3 1 asset options assetoptions maxsupply 100000 marketfeepercent 0 maxmarketfee 0 issuerpermissions assetoptionissuerpermissions overrideauthority flags assetoptionissuerpermissions committeefedasset rawvalue coreexchangerate price description some description echo createasset nameorid some name wif some wif asset asset sendcompletion result in switch result case success let success print success send transaction case failure let error print error while sending transaction confirmnoticehandler notice in switch notice case success let success print transaction confirmed case failure let error print transaction didn t confirmed issue asset swift func issueasset echo issueasset issuernameorid some name wif some wif asset 1 3 87 amount 1 destinationidorname some name sendcompletion result in switch result case success let success print success send transaction case failure let error print error while sending transaction confirmnoticehandler notice in switch notice case success let success print transaction confirmed case failure let error print transaction didn t confirmed contracts create contract swift func createcontract let bytecode some bytecode echo createcontract registrarnameorid some name wif some wif assetid 1 3 0 amount nil assetforfee nil bytecode bytecode supportedassetid nil ethaccuracy nil parameters nil sendcompletion result in switch result case success let success print success send transaction case failure let error print error while sending transaction confirmnoticehandler notice in switch notice case success let success print transaction confirmed case failure let error print transaction didn t confirmed call contract swift func callcontract echo callcontract registrarnameorid some name wif some wif assetid 1 3 0 assetforfee nil contratid 1 16 1 methodname some name methodparams sendcompletion result in switch result case success let success print success send transaction case failure let error print error while sending transaction confirmnoticehandler notice in switch notice case success let success print transaction confirmed case failure let error print transaction didn t confirmed query contract swift func querycontract echo querycontract registrarnameorid some name assetid 1 3 0 contratid 1 16 1 methodname some name methodparams result in switch result case success let success print success case failure let error print error | swift echo echo-ios ios | front_end |
altschool-cloud-exercises | altschool cloud exercises a folder containing all my exercises and progress throughout the course of 2nd semester in the cloud engineering track of altschool africa | cloud |
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COMS4995-s20 | applied machine learning spring 2020 materials for the course coms4995 applied machine learning will be posted here you can find more details on the course and an overview of the materials on the course website http www cs columbia edu amueller comsw4995s20 schedule slides are in the slides https amueller github io coms4995 s20 slides subfolder everything in this repository is licensed cc 0 meaning you can do with it whatever you want | ai |
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open-esp-webradio | open esp webradio this project aims to build a webradio based on the esp8266 the goal is to make it controllable via touchscreen this respository and the entire project is very much work in progress hardware the incoming encoded audio stream is buffered in an external spi ram the esp8266 has two hardware spi controllers spi0 aka spi and spi1 aka hspi the esp 12f module that is used here uses spi0 for accessing the spi flash memory that holds the program data here hspi is used for accessing the spi ram since the pins that are regularly used for hspi will be used for talking i2s to the audio dac spi0 and hspi are configured in overlap mode that means that they share the same pins except for the cs line there is an arbiter that selects which spi controller gets to access the pins the spi ram device here is a 23lc1024 which has a capacity of 1 mbit both the esp8266 and the 23lc1024 support quad spi where all data lines sio0 3 are bidirectional so 4 bits are transferred in every clock cycle the audio dac that is used here is the wm8731 the audio data is transferred using i2s via the i2s controller that is built into the esp8266 the configuration of the dac is performed via i2c even though the esp8266 contains an i2c controller it is not used here because the pins were not available since the wm8731 comes with a microphone interface it is included together with the reverse i2s direction the display that is used here is a mi0283qt 240x320 color lcd infos about the adapter board that molds a touchscreen controller as well can be found here https github com watterott mi0283qt adapter both the lcd controller and the touchscreen controller are also sharing the same spi pins as the spi flash and the spi ram both are controlled by the hspi controller the lcd uses a hardware cs but for the touchscreen controller there was no more hardware cs available that is not used for anything else hence gpio16 is used as the cs line for the touchscreen controller schematic mi0283qt adapter https github com svenschwermer open esp webradio raw master hardware schematic png remarks the spi ram is wired incorrectly sio2 and sio3 should be swapped this is fixed in software software to build the software follow the instructions in the open esp webradio repository https github com superhouse esp open rtos to install the required toolchain then simply run make or make flash respectively to compile or flash the image the wifi credentials should be supplied via the file esp open rtos include private ssid config h credits inspired by esp8266 mp3 decoder https github com espressif esp8266 mp3 decoder this project builds upon the following components open esp webradio https github com superhouse esp open rtos libmad https www underbit com products mad license this project is licensed under the terms of the gnu gplv3 see license md license md | esp8266 mp3 webradio glcd esp-open-rtos esp-12f mi0283qt libmad | os |
bor | bor overview bor is the official golang implementation of the polygon pos blockchain it is a fork of geth https github com ethereum go ethereum and is evm compatible upto london fork api reference https camo githubusercontent com 915b7be44ada53c290eb157634330494ebe3e30a 68747470733a2f2f676f646f632e6f72672f6769746875622e636f6d2f676f6c616e672f6764646f3f7374617475732e737667 https pkg go dev github com maticnetwork bor go report card https goreportcard com badge github com maticnetwork bor https goreportcard com report github com maticnetwork bor mit license https img shields io github license maticnetwork bor discord https img shields io discord 714888181740339261 color 1c1ce1 label polygon 20 7c 20discord 20 f0 9f 91 8b 20 style flat square https discord com invite 0xpolygondevs twitter follow https img shields io twitter follow 0xpolygon svg style social https twitter com 0xpolygon installing bor using packaging the easiest way to get started with bor is to install the packages using the command below refer to the releases https github com maticnetwork bor releases section to find the latest stable version of bor curl l https raw githubusercontent com maticnetwork install main bor sh bash s v0 4 0 network node type the network accepts mainnet or mumbai and the node type accepts validator or sentry or archive the installation script does the following things create a new user named bor install the bor binary at usr bin bor dump the suitable config file based on the network and node type provided at var lib bor and uses it as the home dir create a systemd service named bor at lib systemd system bor service which starts bor using the config file as bor user the releases supports both the networks i e polygon mainnet and mumbai testnet unless explicitly specified before the stable release for mainnet pre releases will be available marked with beta tag for deploying on mumbai testnet on sufficient testing stable release for mainnet will be announced with a forum post building from source install go version 1 19 or later and a c compiler clone the repository and build the binary using the following commands shell make bor start bor using the ideal config files for validator and sentry provided in the packaging folder shell build bin bor server config packaging templates mainnet v1 sentry sentry bor config toml to build full set of utilities run shell make all run unit and integration tests shell make test make test integration using the new cli post v0 3 0 release bor uses a new command line interface cli the new cli located at internal cli has been built with keeping the flag usage similar to old cli located at cmd geth with a few notable changes please refer to docs docs section for flag usage guide and example documentation the official documentation for the polygon pos chain can be found here https wiki polygon technology docs pos getting started it contains all the conceptual and architectural details of the chain along with operational guide for users running the nodes new release announcements and discussions can be found on our forum page https forum polygon technology polygon improvement proposals can be found here https github com maticnetwork polygon improvement proposals contribution guidelines thank you for considering helping out with the source code we welcome contributions from anyone on the internet and are grateful for even the smallest of fixes if you d like to contribute to bor please fork fix commit and send a pull request for the maintainers to review and merge into the main code base from the outset we defined some guidelines to ensure new contributions only ever enhance the project quality code in the polygon project should meet the style guidelines with sufficient test cases descriptive commit messages evidence that the contribution does not break any compatibility commitments or cause adverse feature interactions and evidence of high quality peer review code must adhere to the official go formatting https golang org doc effective go html formatting guidelines i e uses gofmt https golang org cmd gofmt testing please ensure that the updated code passes all the tests locally before submitting a pull request in order to run unit tests run make test and to run integration tests run make test integration size the polygon project s culture is one of small pull requests regularly submitted the larger a pull request the more likely it is that you will be asked to resubmit as a series of self contained and individually reviewable smaller prs maintainability if the feature will require ongoing maintenance e g support for a particular brand of database we may ask you to accept responsibility for maintaining this feature pull requests need to be based on and opened against the develop branch pr title should be prefixed with package s they modify e g eth rpc make trace configs optional license the go ethereum library i e all code outside of the cmd directory is licensed under the gnu lesser general public license v3 0 https www gnu org licenses lgpl 3 0 en html also included in our repository in the copying lesser file the go ethereum binaries i e all code inside of the cmd directory are licensed under the gnu general public license v3 0 https www gnu org licenses gpl 3 0 en html also included in our repository in the copying file join our discord server join polygon community share your ideas or just say hi over on discord https discord com invite 0xpolygondevs | matic ethereum go bor | blockchain |
deep-language-networks | deep language networks div align center arxiv https arxiv org abs 2306 12509 blog https medium com friederike niedtner deep language networks stacking llms in trainable layers e7f719bcabde div in this repository you will find the code for deep language networks joint prompt training of stacked llms using variational inference please refer to our paper for further details abstract we view large language models llms as stochastic language layers in a network where the learnable parameters are the natural language prompts at each layer we stack two such layers feeding the output of one layer to the next we call the stacked architecture a deep language network dln we first show how to effectively perform prompt optimization for a 1 layer language network dln 1 we then show how to train 2 layer dlns dln 2 where two prompts must be learnt we consider the output of the first layer as a latent variable to marginalize and devise a variational inference algorithm for joint prompt training a dln 2 reaches higher performance than a single layer sometimes comparable to few shot gpt 4 even when each llm in the network is smaller and less powerful setup clone repo git clone https github com microsoft deep language networks git cd deep language networks installl dependencies conda create n dln python 3 10 conda activate dln pip install e setup data bash scripts setup data sh set your openai api key export your key or put it in your shrc e g export openai api key your key in order to use microsoft azure endpoints in addition to the openai api key you need to set the openai api type openai api base and openai api version the openai api type must be set to azure and the others correspond to the properties of your endpoint setup self hosted models vllm export huggingface id or path to the tokenizer for example meta llama llama 2 70b chat hf from huggingface or path to llama 2 70b chat hf from your local machine then export the openai env vars openai api base and openai api key remember to unset openai api type and openai api version if you have set them before export tokenizer path path to tokenizer export openai api key empty export openai api base http 127 0 0 1 8000 v1 unset openai api type unset openai api version running experiments please see the variational inference readme projects vi dln readme md for information on how to run experiments limitations when it comes to large scale natural language models there are particular fairness and responsible ai issues to consider people use language to describe the world and to express their beliefs assumptions attitudes and values as a result publicly available text data typically used to train large scale natural language models contains societal biases relating to race gender religion age and other groups of people as well as other undesirable content these societal biases are reflected in the distributions of words phrases and syntactic structures large scale natural language models trained with such data can potentially behave in ways that are unfair unreliable or offensive in turn causing harms while we are fully aware of the limitations of addressing societal issues through technical work we hope that modular approaches like ours will alleviate some of the issues associated with llms like the concentration of power associated with the difficulty to train them we also hope that by facilitating the reusability and adaptivity of such models we shall make them more amenable to a wider variety of use cases however while we discuss the performance of these models on artificial benchmarks we do not address the question of when and how such models should be deployed nor do we offer additional guarantees against their misuse we also emphasize that performance on artificial tasks even if realistic is neither representative of performance in uncontrolled environments nor enough to justify the deployment of these models in high stakes situations please refer to our paper for the specific evaluations we conducted citing deep language networks if you find dlns useful please consider citing this work text article sordoni2023deep title deep language networks joint prompt training of stacked llms using variational inference author alessandro sordoni and xingdi yuan and marc alexandre c t and matheus pereira and adam trischler and ziang xiao and arian hosseini and friederike niedtner and nicolas le roux year 2023 eprint 2306 12509 archiveprefix arxiv primaryclass cs cl contributing this project welcomes contributions and suggestions most contributions require you to agree to a contributor license agreement cla declaring that you have the right to and actually do grant us the rights to use your contribution for details visit https cla opensource microsoft com when you submit a pull request a cla bot will automatically determine whether you need to provide a cla and decorate the pr appropriately e g status check comment simply follow the instructions provided by the bot you will only need to do this once across all repos using our cla this project has adopted the microsoft open source code of conduct https opensource microsoft com codeofconduct for more information see the code of conduct faq https opensource microsoft com codeofconduct faq or contact opencode microsoft com mailto opencode microsoft com with any additional questions or comments trademarks this project may contain trademarks or logos for projects products or services authorized use of microsoft trademarks or logos is subject to and must follow microsoft s trademark brand guidelines https www microsoft com en us legal intellectualproperty trademarks usage general use of microsoft trademarks or logos in modified versions of this project must not cause confusion or imply microsoft sponsorship any use of third party trademarks or logos are subject to those third party s policies | ai |
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design-system | undataforum design system this monorepo contains the design system for united nations world data forum websites undataforum assets https github com undataforum components tree master packages components requires users to sign a waiver of liability undataforum components https github com undataforum components tree master packages components licensed under the mit license https github com undataforum design system blob master packages components license md undataforum preset https github com undataforum components tree master packages preset licensed under the mit license https github com undataforum design system blob master packages preset license md | os |
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Multiverso | multiverso build status https travis ci org microsoft multiverso svg branch master https travis ci org microsoft multiverso multiverso is a parameter server based framework for training machine learning models on big data with numbers of machines it is currently a standard c library and provides a series of friendly programming interfaces and it is extended to support calling from python and lua programs with such easy to use apis machine learning researchers and practitioners do not need to worry about the system routine issues such as distributed model storage and operation inter process and inter thread communication multi threading management and so on instead they are able to focus on the core machine learning logics data model and training for more details please view our website http www dmtk io http www dmtk io build linux tested on ubuntu 14 04 sudo apt get install libopenmpi dev openmpi bin build essential cmake git git clone https github com microsoft multiverso git recursive cd multiverso mkdir build cd build cmake make sudo make install windows open the multiverso sln with visual studio 2013 and build related projects current distributed systems based on multiverso lightlda https github com microsoft lightlda scalable fast lightweight system for large scale topic modeling distributed word embedding https github com microsoft multiverso tree master applications wordembedding distributed system for word embedding distributed word embedding deprecated https github com microsoft distributed word embedding distributed system for word embedding distributed skipgram mixture deprecated https github com microsoft distributed skipgram mixture distributed skipgram mixture for multi sense word embedding microsoft open source code of conduct this project has adopted the microsoft open source code of conduct https opensource microsoft com codeofconduct for more information see the code of conduct faq https opensource microsoft com codeofconduct faq or contact opencode microsoft com mailto opencode microsoft com with any additional questions or comments | ai |
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MidtermsExam | midterms a new flutter project getting started this project is a starting point for a flutter application a few resources to get you started if this is your first flutter project lab write your first flutter app https flutter dev docs get started codelab cookbook useful flutter samples https flutter dev docs cookbook for help getting started with flutter view our online documentation https flutter dev docs which offers tutorials samples guidance on mobile development and a full api reference | front_end |
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Data-Science-Projects | data science real world projects hey data scientist i am learning data science and machine learning with the help of internet here is my some work check out my data science projects including data preprocessing machine learning and deep learning with various type of datasets i created this repo when i was in my initial stage of learning so my apporach is too amature for the problem statements do check my latest repositories connect me twitter https twitter com kuchbhikaran linkedin https www linkedin com in karanshingde gmail karanshingde gmail com tools python numpy pandas matplotlib seaborn sklearn tensorflow and keras google sheets tableau editors google collab jupyter notebook kaggle notebook special thanks google youtube stackoverflow udemy towards data science kaggle linkedin twitter my laptop coding platforms kaggle https www kaggle com karan842 leetcode https leetcode com karanshingde hackerrank https www hackerrank com karanshingde thank you | data-science machine-learning python kaggle deep-learning | ai |
qpc | qp framework https www state machine com img qp banner jpg what s new github release latest by date https img shields io github v release quantumleaps qpc https github com quantumleaps qpc releases latest view qp c revision history at https www state machine com qpc history html note if you re interested in the latest qp c version from github it is recommened that you clone this repo like that git clone https github com quantumleaps qpc recurse submodules depth 1 alternatively you can also download the latest qp c release https github com quantumleaps qpc releases getting started with qp c the most recommended way of obtaining qp c is by downloading the qp bundle https www state machine com downloads which includes qp c as well as the qm modeling tool and the qtools collection the main advantage of obtaining qp c bundled together like that is that you get all components tools and examples ready to go getting started resources qp c tutorial tutorial describes a series of progressively advanced qp c example applications video getting started with qp real time embedded frameworks video provides instructions on how to download install and get started with qp appnote getting started with qp real time embedded frameworks an contains also a tutorial in which you build a simple blinky application about qp c qp c quantum platform in c is a lightweight open source real time embedded framework rtef rtef for building modern embedded software as systems of asynchronous event driven active objects active actors the qp c framework is a member of a qp family consisting of qp c and qp c frameworks which are strictly quality controlled thoroughly documented and commercially licensable lic safer model of concurrency the qp framework family is based on the active object active actor design pattern which inherently supports and automatically enforces the following best practices of concurrent programming keep data isolated and bound to active objects threads threads should hide encapsulate their private data and other resources and not share them with the rest of the system communicate among active object threads asynchronously via event objects using asynchronous events keeps the threads running truly independently without blocking on each other active object threads should spend their lifetime responding to incoming events so their mainline should consist of an event loop that handles events one at a time to completion thus avoiding any concurrency hazards within an active object thread itself this architecture is generally safer more responsive and easier to understand and maintain than the shared state concurrency of a conventional rtos it also provides higher level of abstraction and the correct abstractions to effectively apply modeling and code generation to deeply embedded real time systems hierarchical state machines the behavior of active objects is specified in qp c by means of hierarchical state machines hsm uml statecharts the framework supports manual coding of uml state machines in c as well as automatic code generation by means of the free qm modeling tool qm built in real time kernels the qp c framework can run on bare metal single chip microcontrollers completely replacing a traditional rtos the framework contains a selection of built in real time kernels such as the cooperative qv kernel the preemptive non blocking qk kernel and the preemptive blocking qxk kernel that provides all the features you might expect from a traditional rtos native qp ports and ready to use examples are provided for major cpus such as arm cortex m m0 m0 m3 m4 m7 traditional rtos os qp c can also work with a traditional rtos such as threadx freertos embos uc os ii and ti rtos as well as with embedded linux posix and windows popularity and maturity with 20 years of continuous development over 350 commercial licensees cust and many times more open source users worldwide the qp frameworks are the most popular such offering on the market they power countless electronic products ranging from implantable medical devices to complex weapon systems qp c licensing qp c is licensed under the sustainable dual licensing model lic in which both the open source software distribution mechanism and traditional closed source software distribution models are combined note if your company has a policy forbidding open source in your product all qp frameworks can be licensed commercially lic in which case you don t use any open source license and you do not violate your policy qp c documentation the online html documention for the latest version of qp c is located at https www state machine com qpc the offline html documentation for this particular version of qp c is located in the sub folder html html to view the offline documentation open the file html index html html index html in your web browser how to get help free support forum https sourceforge net p qpc discussion 668726 bug reports https sourceforge net p qpc bugs feature requests https sourceforge net p qpc feature requests quantum leaps website https www state machine com quantum leaps licensing https www state machine com licensing info state machine com mailto info state machine com how to help this project if you like this project please give it a star in the upper right corner of your browser window github star https www state machine com img github star jpg rtef https www state machine com rtef qp https www state machine com products qp qp c https www state machine com qpc qp c https www state machine com qpcpp qm https www state machine com products qm active https www state machine com active object hsm https www state machine com fsm hsm lic https www state machine com licensing cust https www state machine com customers an https www state machine com doc an getting started with qp pdf tutorial https www state machine com qpc gs tut html video https youtu be o7er6 vqih0 | embedded embedded-c rtos statechart state-machine event-driven framework arm arm-cortex-m0 arm-cortex-m3 arm-cortex-m7 uml-state-machine samek qp active-object actor-model actor hierarchical-state-machine arm-cortex-m arm-cortex-m4 | os |
InvertedPendulum | inverted pendulum wanna build an inverted pendulum like in this video pendulum movie pictures gifmovie gif https www youtube com watch v 6xe19xnx5l0 t 20s you are in the right place all what you need to known to get an incredible pendulum that jumps and balances is available here i describe how to make the electronic board how to make the shell how to get the other components how to program the firmware how to assemble the pendulum how to connect to the control station software how to calibrate the sensors if you understand french the long way explanation can be found on my blog https jsgonsette github io otherwise keep reading how to make the electronic board pendulum pcb pictures pcb png get the bom first you need all the electronic components on this bom list electronic bom xlsx this kind of components can be found on different sites like farnell http farnell com rs components http www rs online com digikey https www digikey com make the pcb you need to make the pcb whose plans are given by the different files in this directory electronic pcb to be continued soldering of the components refer to this implementation plan electronic pcb pcb pdf to solder the different components on the both faces with enough dexterity and patience all the components could be soldered by hand with a soldering iron there are two exceptions u400 and u401 are only available in lga package which means no weldable legs you have two options for those ones either you are confident enough to use solder paste and an oven or you do it like me and you ask your pcb manufacturer to do it for you this option is ofen available and you can save money by asking them to only solder those two components how to make the shell pendulum shell pictures shell png the shell of the pendulum is composed of three pieces whose plans are given by the three step files in this directory mecanic shell back of the shell holding the pcb and the battery front of the shell holding the motor the hub of the flywheel they have to be 3d printed you can do it yourself in case you have access to a 3d printer or just use an online service like sculpteo https www sculpteo com you need to upload the three step files then to chose this material nylon pa12 plastic https www sculpteo com en materials plastic material don t go to other materials as it could change the weight of the pendulum weight is important how to get the other components pendulum inventory pictures inventory png some additional parts are still needed before getting a functional pendulum the metallic outer ring of the flywheel it can be ordered on the misumi web site https uk misumi ec com use the reference awsm d d55 v48 t10 in the search box to land on the right page the maxon brushless motor whose reference is ec45 flat 200142 https www maxonmotor com maxon view product 200142 available on rs the lipo battery the model is not so important as long as the physical dimensions and the output voltage are respectively 5x3x1cm and 7 5v a possible choice can be found here https www guixmodel fr modelisme accus et chargeurs accus lipo 2s accu lipo 450mah 2s 30c kryptonium detail seven screws to atttach the pcb in the shell and to tie the two parts of the shell together check this assembly bom assembly 20bom xlsx three screws to attache the motor in the shell check this assembly bom assembly 20bom xlsx the cable to connect the pcb to the battery you have to assemble it yourself check this cables bom mecanic cables 20bom xlsx the cable to connect the pendulum to the pic microcontroller programmer you have to assemble it yourself check this cables bom mecanic cables 20bom xlsx a lipo charger personnaly i m very pleased with the graupner ultramat 14 plus https www graupner de mediaroot files 6464 ultramat 14 plus de en fr it pdf but there are many other ones a microchip programmation device like the pickit 3 https www microchip com developmenttools productdetails pg164130 or the icd 3 https www microchip com developmenttools productdetails dv164035 availabe on farnell for example optional the cable to connect the pendulum to a serial cable you have to assemble it yourself check this cables bom mecanic cables 20bom xlsx optional a usb serial cable how to program the firmware the brain of the pendulum is a small microchip 16bits c you must load the right firmware inside to give life to the pendulum download and install microchip mplab x http microchipdeveloper com ipe installation connect your chip programmer like the pickit 3 or the icd 3 to the electonic board p200 connector with the dedicated cable connect your chip programmer to your computer charge the lipo battery and connect it to the electronic board power up the electronic board by switching the power button the green l301 led should turn on launch the application mplab ipe 1 in the device family field select 16 bit dscs dspic33 2 in the device field select dspic33ep128mc202 3 ensure the tool field displays the name of your chip programmer correctly 4 in the source field browse your computer to select the ipendulum hex firmware available here software binaries firmware ipendulum hex 5 click on connect 6 click on program to flash the microcontroller 7 click on verify to check the microcontroller content integrated programming environment pictures ipe png test your flashed electronic board you can easily check your pcb is fully functional by proceeding as follows connect the motor to the pcb by inserting its electrical flat ribbon inside the j100 socket connectors facing down see picture below connect the charged lipo to the pcb hold the motor in your hand firmly but it must be able to turn freely switch the power button b300 on if everything is ok the motor will turn briefly and stop the red error led l200 should not turn on or blink the meaning of this led is as follows simple blink lipo state of charge too low double blink motor not detected tripple blink could not intialize the gyro device quadruple blink could not initalize the accelerometers device testing the pcb pictures motorconnection jpg how to assemble the pendulum pendulum shell pictures gifassembly gif plug the power cable to the j300 connector on the pcb use four plastic screws to mount the pcb into the back of the shell use the three m3 screws to mount the motor into the front of the shell pay attention to the orientation of the flat ribbon cable mounting instructions pictures mount0 jpg mount the metallic ring around the plastic flywheel hub it should be reasonably tight i had to use a clamping vice drill a 4mm hole through the axis of rotation of the flywheel hub test your drill bit in a stuck of wood before use a drill column for the hole to be straight plug the flywheel on the motor when you push on the flywheel to get it on the axis be sure to apply a vertical force so as not to bend the motor the flywheel should not be able to slip around the axis use a bit of strong glue if needed insert the motor electrical ribbon cable in the pcb connector connectors facing down mounting instructions pictures mount1 jpg assemble the two parts of the shell together and fix them with the three remaining screws put the lipo battery in place and plug it to the power connector img src pictures mount2 jpg width 50 how to connect to the control station software the control station software binaries controlstation ipendulumcs exe is a small program written in c tested on windows only enabling to connect to the pendulum through a serial connection connect a usb serial cable to your computer connect the adapter cable to the usb serial cable and to the pendulum launche the control station software select the menu tools connect to ipendulum selecting the com port corresponding to your usb serial cable power on the pendulum you should get to something like on this picture mounting instructions pictures csnotconnected png by clicking the connect button the software testes the communication by sending a request to the pendulum and check the response if valid the screen will be displayed in color and the drawing of the pendulum will follow the real pendulum movement the panel on the left let you see all the different variables of the running firmware being related to the os or to the pendulum sensors a thumb in the bottom of the screen makes the view switch to different graphs showing all the telemetries they correspond to the different sensors measured on the pendulum connection to the pendulum pictures gifconnectcs gif how to calibrate the sensors calibration of the pendulum is saved in the flash memory of the microcontroller where it survives even when the pendulum is switech off the control station software helps you to calibrate the measured voltage of the lipo tools calibration battery the measured angle of the pendulum tools calibration imu battery voltage calibration only ask you to enter the real voltage of the lipo measured with a voltmeter for the imu the software will ask you to put the pendulum in a succession of different positions just follow the instructions until the end of the procedure you can check the result of this calibration by posing the pendulum on its right of left side on a flat table and by checking in the interface that the angle is close to 45 and 45 this measure can be seen on state estimation field of the left panel | c csharp electronics control microcontroller education rtos 3d-printing kalman-filter pic16 microchip inverted-pendulum lqr-controller | os |
voxelgpt | voxelgpt wish you could search your images or videos without writing a line of code now you can voxelgpt is a fiftyone plugin https docs voxel51 com plugins index html that combines the power of gpt 3 5 https platform openai com docs models gpt 3 5 with fiftyone https github com voxel51 fiftyone s computer vision query language enabling you to filter sort and semantically slice your data with natural language https github com voxel51 voxelgpt assets 12500356 3c2659a4 833d 4634 8d26 9792ab3453cd live demo you can try voxelgpt live at gpt fiftyone ai https gpt fiftyone ai capabilities voxelgpt is capable of handling any of the following types of queries dataset queries querying your dataset fiftyone docs queries querying the fiftyone docs general computer vision queries general computer vision queries when you ask voxelgpt a question it will interpret your intent and determine which type of query you are asking if voxelgpt is unsure it will ask you to clarify querying your dataset https github com voxel51 voxelgpt assets 12500356 5728b067 defc 4db3 8cda ad8da3523cf4 you can ask voxelgpt to search your datasets for you here s some examples of things you can ask retrieve me 10 random samples display the most unique images with a false positive prediction just the images with at least 2 people show me the 25 images that are most similar to the first image with a cat under the hood voxelgpt interprets your query and translates it into the corresponding dataset view https docs voxel51 com user guide using views html voxelgpt understands the schema of your dataset as well as things like evaluation runs https docs voxel51 com user guide evaluation html and similarity indexes https docs voxel51 com user guide brain html similarity it can also automatically inspect the contents of your dataset in order to retrieve specific entities querying the fiftyone docs https github com voxel51 voxelgpt assets 12500356 a32d4856 612c 4407 8dde 6bad5efb0357 voxelgpt is not only a pair programmer it is also an educational tool voxelgpt has access to the entire fiftyone docs https docs voxel51 com which it can use to answer fiftyone related questions here s some examples of documentation queries you can ask voxelgpt how do i load a dataset from the fiftyone zoo what does the match stage do can i export my dataset in coco format general computer vision queries https github com voxel51 voxelgpt assets 12500356 294b53f8 9398 4e6a b923 56c7a9684f1d finally voxelgpt can answer general questions about computer vision machine learning and data science it can help you to understand basic concepts and learn how to overcome data quality issues here s some examples of computer vision queries you can ask voxelgpt what is the difference between precision and recall how can i detect faces in my images what are some ways i can reduce redundancy in my dataset installation if you haven t already install fiftyone https github com voxel51 fiftyone shell pip install fiftyone you ll also need to provide an openai api key create one https platform openai com account api keys shell export openai api key xxxxxxxx app only use if you only want to use voxelgpt in the fiftyone app https docs voxel51 com user guide app html then you can simply install it as a plugin https docs voxel51 com plugins index html shell fiftyone plugins download https github com voxel51 voxelgpt fiftyone plugins requirements voxel51 voxelgpt install local use development if you want to directly use the voxelgpt module or develop the project locally then you ll want to clone repository shell git clone https github com voxel51 voxelgpt cd voxelgpt install the requirements shell pip install r requirements txt and make the plugin available for use in the fiftyone app by symlinking it into your plugins directory shell symlinks your clone of voxelgpt into your fiftyone plugins directory ln s pwd fiftyone config plugins dir voxelgpt fiftyone teams want to add voxelgpt to your fiftyone teams https voxel51 com fiftyone teams deployment you can instructions here fiftyone teams md using voxelgpt in the app you can use voxelgpt in the fiftyone app by loading any dataset py import fiftyone as fo import fiftyone zoo as foz dataset foz load zoo dataset quickstart session fo launch app dataset and then either clicking on the openai icon above the grid pressing the icon next to the samples tab and choosing voxelgpt https github com voxel51 voxelgpt assets 12500356 fbaccb6f dc7f 43d7 9da3 adb4062c398b for example try asking the following questions what are some popular model architectures for computer vision how do i search for specific objects in my dataset show me predicted airplanes pro tip use the now keyword keywords to incorporate your previous prompts as context for your next query you can also run voxelgpt as an operator https docs voxel51 com plugins index html fiftyone operators by pressing the key on your keyboard and selecting ask voxelgpt from the list this will open up a small modal where you can type in your query using voxelgpt in python if you ve installed locally local use development you can also directly interact with voxelgpt via python interactive sessions you can use ask voxelgpt interactive to launch an interactive session where you can converse with voxelgpt via input prompts py import fiftyone as fo import fiftyone zoo as foz from voxelgpt import ask voxelgpt interactive dataset foz load zoo dataset quickstart session fo launch app dataset ask voxelgpt interactive dataset session session pro tip use the now keyword keywords to incorporate your previous prompts as context for your next query as usual you can prompt voxelgpt with any combination of dataset documentation and general computer vision queries for example a conversation might look like you what is the difference between precision and recall voxelgpt precision and recall are two important metrics used to evaluate the performance of a machine learning model in classification tasks precision measures the proportion of true positive predictions among all positive predictions made by the model recall on the other hand measures the proportion of true positive predictions among all actual positive instances in the dataset in other words precision is the ability of the model to correctly identify positive instances while recall is the ability of the model to identify all positive instances a high precision means that the model is making very few false positive predictions while a high recall means that the model is able to identify most of the positive instances in the dataset it is important to balance precision and recall when evaluating a model s performance a model with high precision but low recall may be missing important positive instances while a model with high recall but low precision may be making too many false positive predictions in the context of the fiftyone library precision and recall can be computed using the fiftyone utils metrics module which provides functions for computing various classification metrics for example the fiftyone utils metrics binary classification function can be used to compute precision and recall for binary classification tasks you does fiftyone integrate with label studio voxelgpt yes fiftyone integrates with label studio the integration allows you to easily upload your data directly from fiftyone to label studio for labeling you can get started with label studio through a simple pip install to get a local server up and running fiftyone provides simple setup instructions that you can use to specify the necessary account credentials and server endpoint to use fiftyone provides an api to create projects upload data define label schemas and download annotations using label studio all programmatically in python all of the following label types are supported for image datasets classification detections instance segmentations polygons and polylines keypoints scalar fields and semantic segmentation sources https docs voxel51 com integrations index html https docs voxel51 com integrations labelstudio html you show me predicted airplanes voxelgpt identified potential algorithms evaluation no evaluation runs found identified potential fields predictions identified potential label classes predictions airplane identified potential view stages match filter labels match labels exclude labels filter field okay i m going to load dataset filter labels predictions f label airplane you now only show me the first 10 samples voxelgpt identified potential algorithms evaluation no evaluation runs found identified potential fields predictions identified potential label classes predictions airplane identified potential view stages match limit limit labels skip sort by okay i m going to load dataset match f predictions detections label contains airplane limit 10 you exit in interactive mode voxelgpt automatically loads any views it creates in the app and you can access them via your session https docs voxel51 com user guide app html sessions object py print session view count predictions detections single queries you can also use ask voxelgpt to prompt voxelgpt with individual queries py from voxelgpt import ask voxelgpt ask voxelgpt does fiftyone integrate with cvat yes fiftyone integrates with cvat which is an open source image and video annotation tool you can upload your data directly from fiftyone to cvat to add or edit labels you can use cvat either through the hosted server at app cvat ai or through a self hosted server in either case fiftyone provides simple setup instructions that you can use to specify the necessary account credentials and server endpoint to use the tight integration between fiftyone and cvat allows you to curate and explore datasets in fiftyone and then send off samples or existing labels for annotation in cvat with just one line of code to use cvat you must create an account on a cvat server by default fiftyone uses app cvat ai if you haven t already go to app cvat ai and create an account now another option is to set up cvat locally and then configure fiftyone to use your self hosted server a primary benefit of setting up cvat locally is that you are limited to 10 tasks and 500mb of data with app cvat ai sources https docs voxel51 com integrations cvat html examples https docs voxel51 com tutorials cvat annotation html annotating datasets with cvat https docs voxel51 com tutorials cvat annotation html setup https docs voxel51 com integrations index html fiftyone integrations when voxelgpt creates a view in response to your query it is returned py import fiftyone as fo import fiftyone zoo as foz dataset foz load zoo dataset quickstart view ask voxelgpt show me 10 random samples dataset identified potential view stages match limit skip take sort by okay i m going to load dataset take 10 keywords voxelgpt is trained to recognize certain keywords that help it understand your intent keyword meaning show display tells voxelgpt that you want it to query your dataset and display the results docs how fiftyone tells voxelgpt that you want it to query the fiftyone docs now use your chat history as context to interpret your next query for example if you ask show me images with people and then ask now show me the 10 most unique ones voxelgpt will understand that you want to show the 10 most unique images with people help prints a help message with usage instructions reset resets the conversation history exit exits interactive python sessions contributing contributions are welcome check out the contributions guide contributing md for instructions how does it work voxelgpt uses openai s gpt 3 5 model https platform openai com docs models gpt 3 5 to generate answers including python code openai s text embedding ada 002 model https platform openai com docs guides embeddings embedding models to embed input text prompts langchain https github com hwchase17 langchain provides the connective tissue for the application fiftyone s plugin framework https docs voxel51 com plugins index html to provide the interactive panel in the fiftyone app https docs voxel51 com user guide app html limitations media types voxelgpt currently only supports image datasets we re working on adding support for videos and other media types examples this implementation is based on a limited set of examples so it may not generalize well to all datasets the more specific your query the better the results will be if you find that the results are not what you expect please let us know view stages the current implementation supports most fiftyone view stages https docs voxel51 com user guide using views html but certain stages like concat mongo and geo within are not yet supported we re working on it about fiftyone if you ve made it this far we d greatly appreciate if you d take a moment to check out fiftyone https github com voxel51 fiftyone and give us a star fiftyone is an open source library for building high quality datasets and computer vision models it s the engine that powers this project thanks for visiting join the community if you want join a fast growing community of engineers researchers and practitioners who love computer vision join the fiftyone slack community https slack voxel51 com | artificial-intelligence chatgpt computer-vision data-science deep-learning langchain llm machine-learning openai python fiftyone | ai |
ros_azure_iothub | azure iot hub for ros this ros package works with the microsoft azure iot hub service to relay telemetry messages from the robot to azure iot hub or reflect properties from the digital twin to the robot using dynamic reconfigure prerequisites to use this ros node on your robot you will need azure iot hub service and at least one device registered under iot hub see more on quickstart send telemetry from a device to an iot hub and read the telemetry from the hub with a back end application https docs microsoft com en us azure iot hub quickstart send telemetry c ros installation for windows environment check ros on windows https aka ms ros for ubuntu linux environment check ubuntu install of ros http wiki ros org noetic installation ubuntu how to build ros on windows here is an example how to build it for ros on windows batchfile source ros environment c opt ros noetic x64 setup bat create catkin workspace folders mkdir catkin ws src pushd catkin ws checkout required ros package sources pushd src git clone https github com ms iot abseil cpp b init windows git clone https github com facontidavide ros type introspection git clone b noetic devel recursive https github com microsoft ros azure iothub popd install system dependencies rosdep update rosdep install from paths src ignore src r y build it and source install environment catkin make isolated only pkg with deps roscpp azure iothub install install isolated setup bat how to build ubuntu linux install here is an example how to build it for ubuntu ros linux install bash source ros environment source opt ros melodic setup bash create catkin workspace folders mkdir catkin ws src p pushd catkin ws catkin init workspace src checkout required ros package sources pushd src git clone recursive https github com microsoft ros azure iothub popd install azure iot sdk as debian sudo add apt repository ppa aziotsdklinux ppa azureiot update apt to refresh package registries sudo apt update sudo apt install y azure iot sdk c dev install system dependencies rosdep update rosdep install from paths src ignore src r y build it and source install environment chmod a x src ros azure iothub dynamic tutorials cfg tutorials cfg catkin make install source install setup bash deployment iot hub for telemetry reporting or reported properties channel azure iot hub maintains a device twin for each device that you connect to iot hub device twins are json documents that store device state information including metadata configurations and conditions we are using desired properties as a channel to ask our ros node what ros topics to report the messages received from these ros topics can either be reported through the telemetry channel or through the reported property channel on the device twin the telemetry channel is designed for high bandwidth data and the history of messages sent over this channel are stored the reported property channel is designed for low bandwidth data and it advertises only the latest message for each topic the device twin subscribes to here is a json example to report rosout via telemetry and initialpose via reported properties json deviceid deva properties desired ros relays 1 topic rosout relay method telemetry 2 topic initialpose relay method reported add the ros relays block to the device twin use the client side deployment step to connect to your device you can run the following azure powershell cmdlet to wait for events from iot hub bash az iot hub monitor events hub name youriothubname output table step by step tutorial viewing messages through the reported properties channel step 1 create a new device twin on the azure portal and copy the connection string create device create device step 2 populate the device twin with the desired properties tag adding in the topics you want to subscribe to and the method with which you wish to receive the published messages in this example we are subscribing to the hello topic and we will receive the messages through the reported properties channel desired properties desired properties step 4 locally deploy any ros nodes you wish as an example we will be publishing to the topic hello as the device twin will be subscribing to it publish topic publish topic step 5 launch the azure iot hub ros node and provide the connection string you just copied launch node launch node step 6 back in the azure portal your device twin should be updated with the latest published messages for each topic it is subscribed to img src docs reported properties jpg width 800 deployment iot hub for dynamic configuration dynamic reconfiguration http wiki ros org dynamic reconfigure provides a way to change the node parameters during runtime without restarting the node similar as the telemetry reporting we are using the device twin desired properties as a channel to ask our ros node what dynamic parameters to reconfigure dynamic reconfiguration sample dynamic tutorials here is a json example to reconfigure the parameters of dynamic tutorials node with the new value json deviceid deva properties desired ros dynamic configurations 0 node dynamic tutorials node param str param type string value helloworld 1 node dynamic tutorials node param int param type int value 33 2 node dynamic tutorials node param double param type double value 0 55 3 node dynamic tutorials node param bool param type bool value 1 currently 4 types of parameters can be dynamically reconfigured they are string int double and bool deployment client side this node can be run using roslaunch replacing the value for connection string with the value given by azure iot hub bash roslaunch roscpp azure iothub sample launch connection string hostname sample azure devices net deviceid rosbot sharedaccesskey samplekey this value can also be set in the ros parameter server at roscpp azure iothub node connection string now you can run some other ros scenarios and see the rosout being reported back to iot hub or the node parameters being dynamically reconfigured x 509 certificate authentication by default the ros node will use sas shared access signatures to communicate with iot hub follow the instructions below to use x 509 certificates instead first set up x 509 security in your azure iot hub https docs microsoft com en us azure iot hub iot hub security x509 get started authenticate your x509 device with the x509 certificates complete the steps until you reach authenticate your x 509 device with the x 509 certificates instead the ros node will be used to connect using the x 509 certificates after successfully creating generating or puchasing the x 509 certificates you should have a public key certificate and a private key if the keys were created for test purposes using these instructions they should be stored in two files mydevice private pem and mydevice public pem set the device private key and device public key environment variables to the full file name for the x 509 keys for example on windows run replacing mycertpath mydevice with the path and file name batchfile set device private key c mycertpath mydevice private pem set device public key c mycertpath mydevice public pem to deploy run the following replacing the value for connection string with the value given by azure iot hub launch the node using the x 509 sample launch file roslaunch roscpp azure iothub sample x509 launch connection string hostname hostname sample azure devices net deviceid x509ca test2 x509 true contributing this project welcomes contributions and suggestions most contributions require you to agree to a contributor license agreement cla declaring that you have the right to and actually do grant us the rights to use your contribution for details visit https cla microsoft com when you submit a pull request a cla bot will automatically determine whether you need to provide a cla and decorate the pr appropriately e g label comment simply follow the instructions provided by the bot you will only need to do this once across all repos using our cla this project has adopted the microsoft open source code of conduct https opensource microsoft com codeofconduct for more information see the code of conduct faq https opensource microsoft com codeofconduct faq or contact opencode microsoft com mailto opencode microsoft com with any additional questions or comments link to files create device docs create device gif desired properties docs desired properties gif connection string docs connection string gif publish topic docs publish topic gif launch node docs launch node gif | server |
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Prosumer-TFM | prosumer tfm proposed topic for my master s thesis in software engineering cloud data and it management analysis of iraq as a producer and consumer of energy | cloud |
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capabilities | components of the game architectures an architecture arch is a host system type examples include amd64 arm64 armel armhf i386 mips mipsel powerpc ppc64el s390x sparc host systems an host system host is an implementation of an architecture a host system will have a given amount of storage cpu ram and bandwitdh and comes with an initial cost and an upkeep hosts can be bare metal or cloud and may also be virtual or containers existing within bare metal or the cloud there are various forms of cloud hosts as well hosts have a vendor associated operating systems an operating system os runs on a host not all operating systems can run on all hosts operating systems may have a vendor associated or not platforms a platform plats consists of an an operating system running on a host of an architecture platforms must be deployed by a resource languages languages lang are unique ways to instruct platforms to do tasks not all languages run on all operating systems or even similarly on various operating systems capability capabilities cap are key they re what allow you to do things when implemented capabilities or combinations of capabilities unlock other capabilities capabilities must be maintained by a resource capabilites can be made up of bundled packages or not black box is a special type of capability that comes from a vendor usually with an implied platform requirement some capabilities genereate paper others just enable other capabilities implementations implementations imps are a language specific instance of a capablity implementations must be added to a platform by a resource implementations have a complexity score that must be maintained by a resource with a comparable score to not stop working resources resources can be either an automation or a human or a combination of both automations can augment humans automations an automation is just a capability a sub resource that must be maintained by another resource usually requiring fewer resources humans humans have capability complexity scores not having a high enough score means it ll take longer to instanciate a capability as research will need to be done humans come with an inital cost and an upkeep automations are maintained like any other capability upkeep comes in the form of paper sales and marketing humans are a special kind of human that will increase users per capability research if no resource has a capability at the level required to instantiate something they can either spend time with the associated upkeep spend to research it or you can acquire another resource with that capability research will increase the capability score of that human permanently humans with higher capabilities have higher upkeep requirements and may leave you for greener pastures culture culture will affect how your capabilities are instantiated some cultures are mutually exclusive with others cultures will decide which humans and automations you need to build an maintain capabilities examples include arch vendor os host monoculture polyculture package culture hero culture crunch time agile waterfall flat hiearchy silos cult family open vs closed florr plan 9 5 rowe remote or local contractor culture independent vs vc backed hipster vs new hotness science lab optimize for happiness retalitory culture outsource culture etc initial conditions the game starts with one resource you with a random but humble set of capabilities you must spend time researching the capabilities you d like to instantiate you ll have 250 000 paper to buy implementations and acquire humans turns instantiations upkeep and paper move around during turns if a capability gives you 10 paper user you get that every turn for evey user if a human costs you 10 000 paper that is deducted every turn if an implementation has an upkeep of 100 it is deducted every turn if an implementation has an upkeep of 100 it is deducted every turn 200 turns can be considered roughly a year in game time users these are the consumers that bring in paper there are several types of users you can attract free paying enterprise and institutional each type brings in more paper e g enterprise users pay more than paying users endgame use paper to enlist humans to instantiate capabilities for which the users will give you paper sounds pretty simple right which humans you can enlist will depend on your culture capabilites and how much paper you offer them which users give you paper will depend on which capabilities you offer | server |
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daily-dev-tips | welcome to daily dev tips com license agpl v3 https img shields io badge license agpl v3 blue svg https www gnu org licenses agpl 3 0 about hey there i m chris bongers a full stack remote web developer with 15 years of experience and i ll help you become a web developer with bite sized dev tips live website you can find the website here daily dev tips com https daily dev tips com | blogging css html javascript react webdevelopment | front_end |
Brawl-stars-decompiled-libs | brawl stars decompiled libs well thats ios libs but decompiled thanks to ida pro this may help u to de reverse engineering i am sorry but it is compressed because he is very heavy | os |
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PI | dbot user manual user manual for dbot project initial setup 1 install cassandra and change the following settings in cassandra yaml file authenticator passwordauthenticator roles validity in ms 0 roles update interval in ms 0 credentials validity in ms 0 credentials update interval in ms 0 authorizer cassandraauthorizer 2 clone the repository and run docker 1 git clone this repository 2 go to pi2021django 3 run docker compose up force recreate build 3 optional in case you want to run the server on another address not in 127 0 0 1 1 go to pi2021django project settings p y and change allowed hosts 127 0 0 1 2 also in settings py in databases change host 127 0 0 1 3 in pi2021django docker compose yml change 127 0 0 1 8000 grafana setup 1 go to port 3000 http localhost 3000 http 10 0 12 65 3000 or http 10 0 12 65 3000 http localhost 3000 2 login if asked to with username admin password admin 3 go to configuration data sources 4 click add data source and search for json 5 in url put http 10 0 12 65 3000 str user token grafana http 10 0 12 65 3000 str user token grafana where str user token is the current token you have when you logged in the application 6 click save test a message should appear saying data source is working create dashboard in grafana setup is required 1 go to create dashboard and click add an empty panel 2 click in metric and choose your metric example 1 temperature 3 above the graphic choose your time range 4 on the top right corner click apply add ad hoc filter to a dashboard in grafana setup is required 1 create or edit a dashboard 2 on the top right corner click on the icon to open dashboard settings 3 go to variables and click add variable 4 in type instead of query choose ad hoc filters 5 click update and go back to the dashboard edit panel 6 on the top left corner click on the icon and choose an attribute ex temperature 7 choose an operator ex and type a select value ex 10 8 the graphic should now only show values within the conditions of that new ad hoc filter added api endpoints authentication register new user post name email password bash register user post data example bash name test email test ua pt password randpassword authenticate user post email password bash authenticate user post data example bash email test ua pt password randpassword logout user get where str user token is the token given upon login bash logout user str user token database insert data into user database post where str user token is the token given upon login and str sensorid is the sensorid where the data will be bound to bash insert into db str user token str sensorid post data example bash sensorid 0001 temperature 10 timestamp 2020 06 01 00 02 10 or sensorid 0001 temperature 10 timestamp 2020 06 01 00 02 10 sensorid 0001 temperature 20 timestamp 2020 06 02 00 02 10 query data from user database post where str user token is the token given upon login and str sensorid is the sensorid where the data will be queried from if the sensorid given is all then the query will target all the sensor ids from the user database conditions attributes from ts to ts bash query db str user token str sensorid post data example multiple conditions can be given attributes is the values the query will return if from ts is empty then it will query data from all timestamps bash conditions temperature 5 attributes temperature from ts to ts or conditions temperature 5 temperature 10 attributes temperature from ts 2020 05 31 to ts 2020 06 02 get all attributes from user database get where str user token is the token given upon login bash get all attributes str user token grafana test connection where str user token is the token given upon login bash str user token grafana return available metrics when invoked dropdown metrics when editing a dashboard where str user token is the token given upon login bash str user token grafana search return data based on input data showed in graphic based on metric chosen date range and ad hoc filters where str user token is the token given upon login bash str user token grafana query return annotations where str user token is the token given upon login bash str user token grafana annotations return tag keys for ad hoc filters where str user token is the token given upon login bash str user token grafana tag keys return tag vaues for ad hoc filters where str user token is the token given upon login bash str user token grafana tag values | cassandra django-rest-framework grafana | server |
Computer-Vision-A-Z | udemy computer vision a z website https www udemy com computer vision a z module module 1 face recognition module 2 object detection module 3 gans | ai |
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gopro-usb-tools | warning warning everything here is completely unsupported use everything at your own risk the tools here can very easily kill your camera and cause other problems the author takes no responsibility or liability for anything that may arise as a consequence of using this software use these tools at your own risk introduction everything here is meant for advanced users who have a hard bricked hero2 h3 black camera as in the camera will not turn on at all and who have no other choice but to throw the camera away if you can get warranty support from gopro instead by all means use it but don t try to do some experimental stuff on your own and then try to get warranty support once you start doing anything experimental to the camera including anything written here you have voided your warranty some forum users have gotten these tools to work as a debrick method for their hero2 cameras more information can be found here http goprouser freeforums org booting a hard bricked hero2 camera over usb experimental t11626 html hero3 black thread http goprouser freeforums org booting a hard bricked hero3 black camera over usb danger t14791 html usb command mode these are extremely unofficial and highly experimental tools for booting a hero2 hero3 black camera using the built in usb command mode to enter the built in usb command mode you can do the following 1 disconnect usb from camera 2 remove battery 3 insert battery 4 press and hold the shutter button 5 plug in usb 6 press the power button 7 release the shutter button there might not be anything showing on the screen when the power button is pressed if the charging led was on it might turn off otherwise the camera will still look completely dead but the camera should enumerate as a usb device with a vid pid of 4255 0001 for hero2 or vid pid of 4255 0003 for the hero3 black if so we are in business at this point it is possible to send simple commands over usb they are read from an arbitrary 32 bit word by physical address write to an arbitrary 32 bit word by physical address leave usb command mode and jump to specified physical address these commands can be used to initalize the memory controller load arbitrary code into ram and execute it the code that may be loaded could be of our own creation entirely or it can be one or more sections of the the original gopro firmware which may have been unpacked with https github com evilwombat gopro fw tools so in theory it should be possible to load the hal section and the bootloader or the hal and the rtos section to the camera and jump to it in an attempt to resume an interrupted firmware update or it may be possible to load a linux kernel that was modified for running directly on the camera unlike the existing kernel on the camera which runs in a thread on the rtos however when loading linux or the rtos we still need to load a portion of the bld bootloader to perform basic hw initalization like serial etc another problem is that before the camera software runs the bld bootloader loads the hal section and makes some modifications to it presumably to relocate the hal to a place where the linux kernel and the rtos can get to it since the hal code does not seem to be position independent without these modifications the raw hal section found in the hd2 firmware bin or hd3 03 firmware bin file is not usable so to load and execute anything interesting such as linux or the rtos we need to do the following things load the bld bootloader for things like serial init load a slightly modified fixed up hal load the thing we want to run rtos or linux and possibly an initrd patch the bld bootloader with an instruction to jump to our code rather than trying to boot normally i am not able to include the bld and modified hal binaries directly in the repo but there is a tool to extract the binaries and perform the hal fix ups from the v312 hd2 firmware bin file or the v300 hd3 03 firmware bin file for the hero3 black regardless of which rtos version or linux kernel we are trying to load the bld must come from the v312 version of the hd2 firmware bin file since the offsets and modifications that we make are specific to this version see preparing the necessary bootstrap files below for how to do this the hal comes from the hd2 firmware bin or hd3 03 firmware bin depending on the type of camera but we still use the bld from the hero2 firmware to get the hardware going regardless of camera type compiling and dependencies for windows there are pre built exe files included so there is no need to compile anything for compiling on linux the gpboot program requires libusb 1 0 0 to interact with the camera so you will need to install the libusb 1 0 0 development files before compiling on an ubuntu system you can do this with the following command sudo apt get install libusb 1 0 0 dev once that is installed you can build gpboot and prepare bootstrap with a simple make command make a warning about permissions on some systems you may need to add some kind of a udev rule to make the camera accessible by non root users or you could run gpboot with the sudo command windows version an even more experimental and even less tested but pre built windows version of prepare bootstrap and gpboot is included here these should operate like the linux version hopefully since windows insists on having a specific driver for each usb device i ve included a quick driver for the camera when it is in command mode this driver was made with zadig exe see here http www libusb org wiki windows backend but i know very little about windows and its drivers or how they work still you should be able to open a windows command prompt and use prepare bootstrap exe and gpboot exe as described here miraculously when running gpboot exe linux the usb ethernet device created by the camera does in fact get recognized by windows but i had to unplug replug usb to the camera after linux was booted to make sure the network was fully working for anyone interested the windows version was built using mingw msys if the included windows driver gives you problems or isn t signed etc you should be able to use zadig exe to make and install your own driver the hero2 usb id is 4255 0001 and the hero3 black uses 4255 0003 zadig exe might even try to auto detect the first unknown device preparing the necessary bootstrap files to prepare the bld and modified hal get the v312 hd2 firmware bin file if you have a hero2 or the v300 hd3 03 firmware bin file if you have a hero3 black and execute the following command prepare bootstrap hd2 firmware bin or prepare bootstrap hd3 03 firmware bin this will produce the necessary bld and hal files now gpboot will have the files it needs to bootstrap the camera again this prepare bootstrap commands must be run on the v312 or v300 for h3b firmware update files regardless of what you are actually trying to load and boot in the end to actually boot the camera you can use the gpboot command the gpboot tool supports five loading modes they are load bootloader for hero2 only load rtos for hero2 load rtos for hero3 black load linux for hero2 load linux for hero3 black loading the bootloader bld only on the hero2 gpboot bootloader this will load the bld and the pre modified hal and jump into the bootloader if everything else in the camera is okay the camera should boot normally from this point and you can use some fw update method to reflash the real bootloader in flash if it is somehow damaged if you have serial connected to the camera you can short the tx rx pins to drop into the bootloader console prior to running this command this option only applies to the hero2 camera loading the rtos on the hero2 gpboot rtos rtos file this is probably the most useful booting method but it is also risky this will load the bootloader modified hal and the specified rtos file to the camera the hal rtos will be loaded at high addresses along with a small relocate bin file that knows to copy them where they need to be in case the bootloader tries to overwrite the low memory for some reason the bootloader will be patched in ram to jump to the relocate bin file rather than booting normally to make sure it does not try to load some corrupted damaged version from flash for whatever reason to actually get the rtos files for the hero2 camera see https github com evilwombat gopro fw tools for a utility that can pull them out of existing hd2 firmware bin image the rtos image is not the hd2 firmware bin file in its entirety but is actually a section inside this file since there are several firmware versions available there are several rtos images you can use in general it seems like a good idea to try to use the rtos image from the firmware that you were trying to install when the camera got bricked so if you were trying to downgrade from v222 to v124 it makes sense to use the rtos from the v222 firmware but i don t have enough data to say what works best to save you the trouble of running the fw parser the following dd commands should be able to extract an rtos image from an existing firmware file note that each command is specific to the firmware version and using the wrong command with the wrong firmware file will result in a useless rtos image if you want the rtos from the v124 hd2 firmware bin file dd if hd2 firmware bin skip 213248 conv notrunc of rtos v124 bin count 6344704 bs 1 if you want the rtos from the v198 hd2 firmware bin file dd if hd2 firmware bin skip 15862016 conv notrunc of rtos v198 bin count 6246400 bs 1 if you want the rtos from the v222 hd2 firmware file dd if hd2 firmware bin skip 15866112 conv notrunc of rtos v222 bin count 6250496 bs 1 if you want the rtos from the v312 hd2 firmware file dd if hd2 firmware bin skip 15870208 conv notrunc of rtos v312 bin count 6258688 bs 1 also keep in mind that v198 v222 and v312 firmware files have an alternate rtos image as well this is section 3 if you use fwunpacker but i do not know what the difference between the main and the alternate images is if done correctly and if you are lucky the camera will boot up to the point that it will be execute rtos commands from autoexec ash on the sdcard which could possibly be used to restore the camera to a working state keep in mind that sometimes something goes wonky with the a drive on the rtos so it may be necessary to change directory from a to d in autoexec ash before doing any interesting commands cd d i do not have an exact autoexec ash sequence that will reflash the camera to a working state that works 100 of the time but perhaps the autoexec ash on gopro s website is a good start keep in mind that reboot from autoexec ash will not work if the camera is booted using the usb mode meaning that for an update to finish you might have to boot the camera using usb several times with a delay of a few minutes before you turn off the camera and boot again to let the camera do its thing this applies to performing updates as well since the camera does naturally try to reboot once or twice during the update process which again won t work in this mode and you may have to do the reboot by hand loading the rtos on the hero3 black gpboot h3b rtos h3b v300 rtos patched bin this is probably the most useful booting method but it is also risky this will load the bootloader modified hal and the specified rtos file to the camera for the hero3 black the necessary rtos file h3b v300 rtos patched bin is generated by prepare bootstrap so there is no need to ue fwunpacker to create it like we would need to do on the hero2 the rtos file gets patched to get around an unfortunate feature of the rtos where it tries to detect why it was booted and shut down if there isn t a good reason i guess this is needed if the rtos was woken up by the wifi button or something so it could turn on wifi and shut itself down again since the rtos isn t really expecting to be booted over usb it will detect the usb connection and then go into charging mode instead of booting up which is not very useful for debricking so we patch the rtos file a little bit to ignore the bootup reason and just boot up anyway if you run this option the hero3 bld hal and rtos will be loaded in memory and the bld will be patched to jump to our code instead of trying to read the rtos from flash we actually load another small file evilbootstrap bin this file is just a small delay program that will blink the front red led a few times and delay for a few seconds before jumping to the rtos the reason for loading this little delay is to give the user the opportunity to disconnect usb from the camera after the loading is complete but before the rtos starts running if we don t do this the rtos will detect the usb connection and go into usb storage mode rather than booting normally which is not very useful so as soon as the rtos loading gets to 100 and the red light starts blinking you can unplug usb and the rtos will try to boot within a few seconds i expect the rtos to be largely non functional since the dsp won t be loaded or running but the rtos might in theory be able to read the update cmd file off the sdcard or autoexec ash loading linux on the hero2 gpboot linux this is probably the most advanced booting method and the least useful this command will load a pre build linux kernel zimage and a pre built initrd initrd lzma to the camera and boot them the front led should show a heartbeat pattern and the camera should show up as a newly detected usb ethernet device once that happens you can telnet to the camera on address 10 9 9 1 and hopefully get a little linux shell this may allow you to examine the state of the flash also cat proc mtd and be able to do linux commands interactively it is my hope that this can be a useful method to restore the flash on a camera that is otherwise totally wiped but at the moment there is no known way to reflash the camera from within linux that has worked but i haven t really tried this all that much i did include nanddump and nandwrite into the busybox build and they might come in handy just be careful how the state of the flash relates to the crcs in the partition table ptb also mtd1 is still not quite clear to me either there should also be kernel messages and a shell on the camera s serial port at 115200 baud the sdcard slot should be working as well with the card being accessible via dev mmcblk0 or dev mmcblk0p1 etc the kernel commandline options are hard coded into gpboot c and if you are advanced enough that you want to change them you can modify the file and rebuild if you want to build your own kernel see sources sources txt the kernel here is basically the kernel that was posted on gopro s website http gopro com support open source with some modifications to make it actually compile and some fixes see sources for the patches applied to the kernel on top of gopro s tarball there should be a kernel config file in there as well there is also a busybox config file but i did not modify busybox and you can get the source from busybox net see sources txt loading linux on the hero3 black gpboot h3b linux this is essentially the same as the hero2 linux method described above only it will load a kernel zimage a7 which works on the hero3 black recent updates have allowed the hero3 black to be booted without relying on hero2 firmware which was a long overdue fix thanks to forum user narcoticrex for mailing me a bricked hero3 black which allowed me to dig deep enough to make this possible why did i use lzma as the compression method over the more widely used gzip it seems to result in smaller files which means shorter times needed to load the stuff over usb well that s that have fun be careful and again do everything at your own risk and don t blame me for anything that goes wrong but i hope someone can find this stuff useful and can make a reliable hard debrick method evilwombat | os |
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dotfiles-old | overview this is a complete development configuration using git vim tmux i3 and bash or zsh it should be installable in any nix bash system though the software tools themselves will need to be installed by your system s package manager demo http giant gfycat com plushcalmflamingo gif http gfycat com plushcalmflamingo try it before you buy err use it to test drive the environment minus i3 before committing install vagrant http www vagrantup com build an image with this repo pre installed and ssh in git clone https github com alanctkc dotfiles old git cd dotfiles old vagrant up vagrant ssh you can of course just keep this box installed and do your development in there you ll just want to change your git name and email in gitconfig to your own first features shell aliases gst git status gad git add gbr git branch gcm git commit gdi git diff gdt git difftool gco git checkout glo pretty git log gpv switch to previous git branch to create tmux session named after current directory to name create tmux session with name ta name attach to tmux session with tab completion tl list tmux sessions mkve name make a new virtualenv wo name work on a virtualenv with tab completion py python ipy ipython fl flake8 rn ranger xf extract various archive file types vim plugins vundle https github com gmarik vundle vim plugin manager ctrlp https github com kien ctrlp vim quickly call files into buffers vim handlebars https github com nono vim handlebars handlebars template compatibility and syntax vim jinja2 syntax https github com glench vim jinja2 syntax jinja2 template compatibility and syntax python mode https github com klen python mode python niceties wrapping etc syntastic https github com scrooloose syntastic syntax and coding convention checker tcomment vim https github com tomtom tcomment vim easy comment uncomment vim airline https github com bling vim airline pretty status bar vim bundle mako https github com sophacles vim bundle mako mako template compatibility and syntax vim colorschemes https github com flazz vim colorschemes lots of color options vim fugitive https github com tpope vim fugitive git branches and features vim golang https github com jnwhiteh vim golang go compatibility and syntax vim less https github com groenewege vim less less compatibility and syntax vim surround https github com tpope vim surround surround text motion vim unimpaired https github com tpope vim unimpaired useful extra motions matchit https github com tmhedberg matchit use to jump around html and other extras python matchit https github com voithos vim python matchit use to jump around python code vim sneak https github com justinmk vim sneak quickly jump to characters emmet vim https github com mattn emmet vim html expansion from selectors jedi vim https github com davidhalter jedi vim python autocomplete and function prototypes neocomplete https github com shougo neocomplete vim miscellaenous autocomplete install clone the repository to a permanent home configuration files will be symlinked git clone https github com alanctkc dotfiles old git cd dotfiles old bootstrap sh options git name name specify the full user name for git configuration git email email specify the full user email for git configuration no virtualenv exclude virtualenvwrapper installation using virtualenv burrito no bash exclude bash configuration no zsh exclude zsh configuration no git exclude git configuration no i3 exclude i3 configuration no vim exclude vim configuration no tmux exclude tmux configuration no ipython exclude ipython configuration backups by default backups of your current dotfiles are created at filename dotbackup to delete the backups bootstrap sh delete backups updating bootstrap sh update software ubuntu sudo apt get install git vim nox zsh tmux i3 ranger python python dev python setuptools curl mac os x xcode install command line tools homebrew http mxcl github io homebrew http mxcl github io homebrew brew install python git zsh tmux ranger brew install vim with lua override system python with hombrew version if necessary cd system library frameworks python framework versions sudo mv current current bak sudo ln s usr local cellar python 2 7 3 frameworks python framework versions 2 7 current python tools ipython is a fantastic python interactive shell and flake8 lets vim show you where you re not adhering to python syntax or coding style sudo easy install pip sudo easy install ipython sudo easy install flake8 | front_end |
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frwgan-eccv18 | multi modal cycle consistent generalized zero shot learning cycle wgan eccv 18 paper download paper http openaccess thecvf com content eccv 2018 papers rafael felix multi modal cycle consistent generalized eccv 2018 paper pdf code for model presented on our paper accepted on european conference on computer vision 2018 abstract in generalized zero shot learning gzsl the set of classes are split into seen and unseen classes where training relies on the semantic features of the seen and unseen classes and the visual representations of only the seen classes while testing uses the visual representations of the seen and unseen classes current methods address gzsl by learning a transformation from the visual to the semantic space exploring the assumption that the distribution of classes in the semantic and visual spaces is relatively similar such methods tend to transform unseen testing visual representations into one of the seen classes semantic features instead of the semantic features of the correct unseen class resulting in low accuracy gzsl classification recently generative adversarial networks gan have been explored to synthesize visual representations of the unseen classes from their semantic features the synthesized representations of the seen and unseen classes are then used to train the gzsl classifier this approach has been shown to boost gzsl classification accuracy but there is one important missing constraint there is no guarantee that synthetic visual representations can generate back their semantic feature in a multi modal cycle consistent manner this missing constraint can result in synthetic visual representations that do not represent well their semantic features which means that the use of this constraint can improve gan based approaches in this paper we propose the use of such constraint based on a new regularization for the gan training that forces the generated visual features to reconstruct their original semantic features once our model is trained with this multi modal cycle consistent semantic compatibility we can then synthesize more representative visual representations for the seen and more importantly for the unseen classes our proposed approach shows the best gzsl classification results in the field in several publicly available datasets citation inproceedings felix2018multi title multi modal cycle consistent generalized zero shot learning author felix rafael and kumar bg vijay and reid ian and carneiro gustavo booktitle european conference on computer vision pages 21 37 year 2018 organization springer dependencies in order to reproduce the code please check the requirements txt file attach requirements txt requirements txt in addition it is necessary to clone the repository util https github com rfelixmg util which is an extra dependency for this project with some functionalities package util https github com rfelixmg util https github com rfelixmg util git basic usage the main file for training cycle wgan is train py https github com rfelixmg frwgan eccv18 blob master train py help python train py help example python train py baseroot tmp test train cls 1 train reg 1 train gan 1 architecture file src bash eccv18 awa architecture rwgan json gpu devices 0 gpu memory 0 8 save model 0 savepoints 30 40 300 usage train py h root root namespace namespace gpu devices gpu devices gpu memory gpu memory savepoints savepoints setup setup save model save model save from save from save every save every saveall saveall dbname dbname dataroot dataroot datadir datadir baseroot baseroot description description plusinfo plusinfo sideinfo sideinfo exp directories exp directories auxroot auxroot timestamp timestamp load model load model checkpoint checkpoint checkpoints max checkpoints max validation split validation split metric list metric list checkpoint metric checkpoint metric architecture file architecture file train cls train cls train reg train reg train gan train gan att type att type pre defined experiments we added a few routines that running the entire training which reproduces state of the art results reported in our paper you will find these experiments in src sota dataset name for each dataset we defined 1 train gan sh script to perform the training of cycle wgan 2 generate dataset sh script which uses the trained cycle wgan to generate pseudo samples 3 benchmark sh script to train the fully connected classifier to perform gzsl classification 4 tester sh script which uses the trained cycle wgan to generate pseudo samples 5 architecture cycle wgan json architecture file for cycle wgan 6 architecture fully connected json architecture file for classifier running make sure to adjust the paths and gpu usage parameters bash src sota train gan sh datasets original files download dataset https cvml ist ac at awa2 https cvml ist ac at awa2 this dataset provides a platform to benchmark transfer learning algorithms in particular attribute base classification and zero shot learning it can act as a drop in replacement to the original animals with attributes awa dataset as it has the same class structure and almost the same characteristics in addition on this website you will find cub sun flo dataset in h5file in order to run our experiments and facilitate visualization of the dataset we introduce the gzsl datasets in h5file format you can download the datasets cub sun flo and awa1 in the h5file format which can be downloaded dataset zip https drive google com open id 1cj hl5f9lon4l 53vhu3 zfv0in2ahyi 3gb in zip file alternativelly run the following bash lines wget https drive google com open id 1cj hl5f9lon4l 53vhu3 zfv0in2ahyi o data datasets zip unzip data datasets zip d data hdf5 file the current code uses a hdf5 structure to organize the dataset in order to facilitate the display of the dataset you might want to use hdfview 2 9 for linux users initial setup the general setup for running the experiments can be achieve running the following bash lines git clone https github com rfelixmg frwgan eccv18 git cd frwgan eccv18 git clone https github com rfelixmg util git conda install requirements txt wget https drive google com open id 1cj hl5f9lon4l 53vhu3 zfv0in2ahyi o data datasets zip unzip data datasets zip d data | ai |
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CoLLaMA | collama a multilingual instruction dataset and large language model for code license https img shields io badge license apache 2 0 green svg https github com tatsu lab stanford alpaca blob main license python 3 9 https img shields io badge python 3 9 blue svg https www python org downloads release python 390 english readme zh md this is the repository for the collama project which aims to build a multilingual chinese and english instruction tuning dataset and large language model for coding tasks p align center width 100 img src https i postimg cc j7ds1tw6 collama jpg width 40 height 20 p overview current code instruction datasets which are essential for instruction tuning tasks are often disorganized monolingual and single programming language focused while covering an insufficient variety of tasks open source datasets for instruction tuning in coding tasks are also scarce for this end we propose this project with the following advantages multilingual dataset our dataset incorporates code samples from a multitude of programming languages including java python c c go php javascript and ruby et al it also presents code instructions in both chinese and english enabling the model to learn in various programming language and spoken language contexts and thereby enhancing its generalization ability task diversity the dataset spans a broad range of coding tasks such as code summarization code generation code search and others it incorporates tasks with varying complexities and requirements from beginner to advanced levels this comprehensive approach ensures our instructions can handle different types of coding tasks and covers a broad spectrum of programming skills and knowledge multi programming paradigms the project includes code examples from different programming paradigms such as procedural object oriented functional and event driven programming this wide coverage provides the instruction tuning model with a varied set of coding tasks to learn from and generate instructions for real world code examples the dataset incorporates code snippets or excerpts from actual projects or forums such as stackoverflow and github to present more realistic and practical coding tasks this aids the instruction tuning model in generating instructions applicable to real world scenarios quality assurance we are committed to providing an accurate and high quality dataset for each coding task for instance the instruction dataset for code search extracted from programming posts on stackoverflow q a sites is rigorously filtered and cleaned to ensure its usability in real q a applications the repository contains the following the mulco used for fine tuning the model the code for fine tuning the model model weight the code for evaluation dataset release data mid train en data and data mid train cn data contains around 88k instruction following data used for fine tuning the collama model this file is a list of dictionaries each dictionary contains the following fileds instruction describes the task that the model should perform input optional code or context for the task for example if the instruction is please summarize this php code the input is the php code output the answer to the instruction all data in our collection is formatted into the same templates where each sample is as follows instruction string input string may be empty output string due to the different code tasks we choose which filed to generate with gpt 3 5 turbo or human unlike self struct technology to generate data most of the code in our data comes from the real world whereas most instruction choices are generated by gpt 3 5 turbo the detailed process of data processing is described in the next section dataset collection processing it includes 8 datasets for 8 diversited code tasks covering the following scenarios code generation data code generation according to the natural languages input by the user the corresponding code is generated code summarization data code summarization it aims to generate concise and readable summaries or description of source code it involves automatically generating human readable explations or summaries of code snippets functions or entire programs code search data code search code to code data code search code to code clone detection given a piece of code find another piece of code that is semantically related to it defect detection given a source code the task is to clarify what the specific defect of the code is this include common errors such as null pointer dereferences array out of bounds memory leaks etc code completion line level complete the unfinished line given previous context code repair it aims to automatically fix bugs in the code code translation code translation refers to the process of converting source code from one programming language to another it involves transforming the syntax structure and semantics of the original code while preserving its functionality and behavior query to code data code search query to code given a natural language query and mutiple code snippets the task is to search source code that its function matches the natural languag query a brief summary of mulco is given below table border 1 width 600 align center tr bgcolor d3d3d3 td colspan 3 align center task td td align center source dataset name td td align center num td td align center lang td td align center programming lang td tr tr td colspan 3 rowspan 2 align center code summarization td td align center codesearchnet td td align center 10k td td align center en td td align center go java javascript php python ruby td tr tr td align center codesearchnet td td align center 10k td td align center cn td td align center go java javascript php python ruby td tr tr td colspan 3 rowspan 3 align center code generation td td align center codesearchnet td td align center 10k td td align center en td td align center go java javascript php python ruby td tr tr td align center codegpt td td align center 20k td td align center cn td td align center c c c go java javascript php python ruby td tr td align center codesearchnet td td align center 5k td td align center cn td td align center go java javascript php python ruby td tr tr td rowspan 7 align center code search td td rowspan 5 align center code to code td td align center clone detection td td align center bigclonebench td td align center 10k td td align center en td td align center java td tr tr td align center defect detection td td align center devign td td align center 5k td td align center en td td align center c td tr tr td align center code completion line level td td align center codesearchnet td td align center 5k td td align center en td td align center go java javascript php python ruby td tr tr td align center code repair td td align center bug2fix td td align center 5k td td align center en td td align center java td tr tr td align center code translation td td align center codetrans td td align center 5k td td align center en td td align center java c td tr tr td colspan 2 rowspan 2 align center query to code td td align center codepro td td align center 10k td td align center en td td align center python sql td tr tr td align center codepro td td align center 5k td td align center cn td td align center python sql td tr table we mainly obtained datasets from codesearchnet https github com github codesearchnet codexglue https github com microsoft codexglue codegpt https github com zxx000728 codegpt and codepro https github com hoogang codepro processed them to obtain the aforementioned datasets and concentrated them into one dataset data mid all data json finetuning so far considering the influence between different data tasks we currently only use the code generation code summarization code completion code query datasets for fine tuning at the same time we added the codealpaca https github com sahil280114 codealpaca dataset a total of 52k data after filtering the fine tuning process is basically followed firefly https github com yangjianxin1 firefly to reproduce a fine tuned version of qwen please follow the steps below in order to effectively finetune a qwen 7b model we used qlora technology to train on an a100 80gb gpus meanwhile you need to adjust the training parameters according to your gpus and dataset before fine tuning first make sure to install all requirements using bash pip install r requirements txt below is the command to fine tune qwen 7b using our dataset combined with qlora technology on an a100 80g gpu machine bash torchrun nproc per node 1 master port 29502 train qlora py train args file qwen 7b sft lora json the main fine tuning parameters are as follows bash train file data mid train 512 en 52k jsonl num train epochs 1 per device train batch size 6 gradient accumulation steps 2 learning rate 1e 5 max seq length 512 logging steps 50 save steps 500 save total limit 1 lr scheduler type constant with warmup warmup steps 500 lora rank 64 lora alpha 16 lora dropout 0 05 gradient checkpointing true optim paged adamw 32bit fp16 true dataloader num workers 0 save strategy steps weight decay 0 max grad norm 0 3 you can replace train file with your own dataset the above fine tuning command only saves the weight and configuration file of the adapter and needs to merge the weight of the adapter with the base model merge script see merge lora py evaluation todo after fine tuning on 52k data using qlora technique we evaluated this model on humaneval https github com openai human eval the result is as follows table border 1 width 600 align center tr bgcolor d3d3d3 td align center model td td align center dataset td td align center epoch td td align center max length td td align center pass 1 td td align center pass 10 td tr tr td align center qwen 7b td td align center td td align center td td align center td td align center 0 2478 td td align center 0 3836 td tr tr td align center td td align center summary generation completion codealpaca 45k td td align center 1 td td align center 1024 td td align center 0 2567 td td align center 0 3414 td tr tr td align center td td align center summary generation completion codealpaca 43k td td align center 1 td td align center 512 td td align center 0 2658 td td align center 0 3902 td tr tr td align center td td align center summary generation completion codealpaca query 52k td td align center 1 td td align center 512 td td align center 0 2744 td td align center 0 3902 td tr table we used about 26 6m tokens for instruction fine tuning recently released the code llama models family where all models are intialized with llama 2 model weights and trained on 500b tokens from a code heavy dataset among them the evaluation result of codellama 7b on human eval is 29 98 in contrast we only used 26 6m tokens for training but the evaluation result reached 27 44 this is a amazing result since we only use part of the data at present we will release the evaluation results of fine tuning on all the data in the future citation div div align center a target blank gang hu sup 1 sup span emsp a target blank xi wen sup 1 sup span emsp a target blank xin liu sup 1 sup a emsp a href https jimin chancefocus com target blank jimin huang sup 2 sup a emsp a target blank qianqian xie sup 3 sup a emsp div div div align center sup 1 sup school of information science engineering yunnan university emsp sup 2 sup chancefocus amc emsp sup 3 sup school of computer science wuhan university emsp div misc hu2023collama title collama a multilingual instruction dataset and large language model for code author gang hu and xi wen and xin liu and jimin huang and qianqian xie year 2023 div div | ai |
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expressNoteTakerNinthEdition | github repo size https img shields io github repo size stevensjones expressnotetakerninthedition project title expressnotetakerninthedition description an application that can be used to write save and delete notes equiped with an express backend and saves and retrieves note data from a json file table of contents title title description description table of contents tableofcontents prerequisites prerequisites tests tests contributing contributing usage usage license license further contact furthercontact prerequisites none tests none contributing steven jones usage anyone in need of an application that creates and deletes notes perhaps to organize one s thoughts and keep track of tasks one may need to complete license 2020 steven jones all rights reserved further contact feel free to reach out to me with questions involving this project on github at stevensjones https github com stevensjones | server |
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virtuoso-design-system | virtuoso design system validate pr https github com virtru virtuoso design system workflows validate 20pr badge svg release https github com virtru virtuoso design system workflows release badge svg deploy storybook https github com virtru virtuoso design system workflows deploy 20storybook badge svg this repo enables using the virtuoso design system as front end code html css javascript this project is not a common place for library reuse for instance charts and graphs should be added to the app directly for charting we suggest nivo charts https nivo rocks dive into the docs https virtru github io virtuoso design system explore the code https github com virtru virtuoso design system docs the documentation for virtuoso is hosted on github pages https virtru github io virtuoso design system and powered by storybook https storybook js org to run storybook locally shell npm run storybook installing virtuoso is still a work in progress and installation instructions are limited create react app to install with create react app https create react app dev you will need to use craco https github com gsoft inc craco create react app configuration override 1 install craco npm i save dev craco 2 install craco antd plugin npm i save dev craco antd 3 install virtuoso and antd npm i save virtuoso design system antd 4 create a craco config js and add the config 5 use virtuoso config js craco config js https github com gsoft inc craco blob master packages craco readme md configuration const when whendev whenprod whentest eslint modes postcss modes require craco craco const cracoantdesignplugin require craco antd const virtuosotheme require virtuoso design system dist antd module exports plugins plugin cracoantdesignplugin options customizetheme virtuosotheme update the existing calls to react scripts in the scripts section of your package json file to use the craco cli package json scripts start react scripts start start craco start build react scripts build build craco build test react scripts test test craco test in index css need add import virtuoso design system dist design tokens css import virtuoso design system dist bundle cjs css import virtuoso design system dist open sans css import virtuoso design system dist raleway css html font size 62 5 example import react from react import button from virtuoso design system export default function mycomponment return button hi there button design tokens design tokens are the visual design atoms of the design system specifically they are named entities that store visual design attributes we use them in place of hard coded values such as hex values for color or pixel values for spacing in order to maintain a scalable and consistent visual system for ui development salesforce lightning design system https www lightningdesignsystem com design tokens style dictionary https amzn github io style dictionary is a build system that allows you to define design tokens once in a way for any platform or language to consume 1 our design tokens are defined in lib styles style dict tokens as json files 1 read by the config in lib styles style dict config json 1 and built by the command shell npm run style dictionary build 1 which creates lib styles build files for css js or whatever platform needs them 1 you can clear the built tokens with shell npm run style dictionary clean examples examples can be found in examples releasing releases are handled by auto https intuit github io auto 1 please tag your prs release in order for auto to find them 2 then all you have to do is npm run release and you ll get automatic changelog bump npm version publish to npm based on your npm login or npm token in env make a github release based on your gh token in env this works with the magic described in auto shipit docs https intuit github io auto docs generated shipit a static version of the storybook docs are generated automatically before we publish releases to npm development testing updating to develop new components make sure to add components to lib components add helpers and hooks to lib helpers add relevant stories to stories add tests next to the component run locally shell npm run storybook run tests shell npm run test visual regression testing vrt this repository uses loki for vrt to ensure the visual appearance of states of the components does not regress baseline reference images are intentionally checked into this repository in loki reference running vrt locally you can run the vrt tests locally to check to see if your changes have caused visual regressions from the existing baselines for all components based on the loki config in package json shell npm run test vrt for faster results you can run a subset of tests using storiesfilter shell npm run test vrt storiesfilter input any failed tests will be output in loki difference you can inspect any visual differences that are highlighted in these output images if the differences are intended you can update the baselines by following the instructions in the next section updating loki baselines note before performing this step you must first run the vrt once see previous section if you run the tests above and have legitimate changes in the visual appearance of the components you can approve new baselines which will replace the existing baseline images with the new current images shell npm run loki approve this will immediately take all new baseline images from the last test run and replace the existing baseline images if you wish to update a specific test case image only but reject other changes see the loki cli reference https loki js org command line arguments html we recommend only approving new baselines once all unintended visual changes have been fixed then running the command above so no fine grained filtering of new baselines is needed copyright 2020 virtru corporation | os |
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database-engineering | database engineering the repo contains the concepts skillsets and patterns that you can apply in database engineering what s included in this repository you will find acid properties overview of database indexing database partitioning database replication database sharding understanding database cursors concurrency control optimistic and pessimistic b trees in production database systems database system designs differences between a database management system database engine and embedded database overview of database engines such as myisam innodb rocksdb leveldb and more benefits of using one database engine over the other switching database engines with mysql overview of database security homomorphic encryption in database systems getting started to get started simply navigate to the directory of the project or experiment you want to explore and follow the instructions in the readme file each directory contains a detailed explanation of the project and the concepts it demonstrates contributing if you have any suggestions for additions or improvements to the repository please feel free to open a pull request or an issue i am always looking to learn and grow as a web3 developer and appreciate any feedback support if you have any questions or issues while working through the examples please open an issue and i will do my best to help you happy exploring | server |
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edge_detection_ZYNQ | edge detection zynq zynq zynq arm fpga zynq soc xilinx zynq 7000 zynq 7000 processing system ps fpga programble logic pl arm cortex a9 fpga arm fpga zynq7000 ax7020 xc7z020 2clg400i 1 2 ax7020 zynq7000 ps pl xilinx usb cable usb 2 1 5v 2a 3 4gbit 8gbit ddr3 sdram zynq 4 256mbit qspi flash zynq 5 hdmi 1080p 6 usb2 0 host u usb 7 usb2 0 otg pc usb otg 8 usb uart pc 9 33 333mhz ps 50mhz pl 10 2 40 2 54mm zynq pl io 7 tft ad da 11 12 2 54mm zynq ps mio 4 1 2 3 4 roberts 1963 roberts roberts 2x2 roberts 1655867365557 src equ1 png roberts i 1 2 j 1 2 1655867419163 src equ2 jpg prewitt prewitt 8 1655867478422 src equ3 jpg prewitt 1655867497411 src equ4 jpg sobel prewitt sobel 8 sobel sobel 4 2 2 sobel 1655867550436 src equ5 png canny canny canny 1 2 3 4 canny sobel canny sobel 3 ov5640 zynq7000 ax7020 lcd 1655867604517 src system png ov5640 axi4 stream subset converter edge detector ip vdma1 axi stream ddr3 axi interconnect vdma ip vdma0 ddr3 axi stream axi4s vid out ip lcd v tc ip axi dynclk ip lcd 1655867650439 src structure jpg pwm 1655867681848 src pmw png block design src block design jpg alinx ov5640 ip rgb565 ax4 stream cmos 8 16bit 8 16 rgb565 rgb565 2 cmos in axi4s rgb565 axi4 stream xilinx video in to axi4 stream ip ip rgb565 axi vmda1 vdma 8 sdk lcd 800 480 vga modes h v tc ip lcd 1655867745060 src code1 png sensor sensor 1655867764733 src code2 png pwm set pwm frequency vivado 100mhz pwm hz set pwm duty 1655867788533 src code3 png edge detector 1655867810350 src code4 png 1655867831228 src code5 png threshold 0 rgb grayimg grayimg split0 split1 sobelimg x sobelimg y sobelimg rgb 1655867921267 src result1 png threshold 0 20 1655868064914 src result2 png | os |
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tcnj-madc-resources | tcnj mobile application development club welcome to tcnj madc s official github repo where you can find club announcements and resources from tutorials given at meetings this semester meetings will be held every wednesday from 4 30 pm to 5 30 pm in the aimm 223 please note that we will be meeting in aimm 223 until further notice since we ll be able to access xcode there this week s meeting free project session this week s meeting will take place on wednesday november 18 at 4 30 in aimm 223 come to join the trading card inventory tracker app team or work on an app idea of your own feel free to use the time to bounce ideas around find others to work with you or get help with launching your app idea the rest of the weekly meetings for this semester will be taking this format | front_end |
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CARduino | carduino the code and design for james libbey s freshman embedded systems project created in collaboration with matt hawkins using an arduino construct the circuit shown in circuitdiagram pdf following the standard pin connections for the lcd screen then download the code in carduino1 0 ino onto the arduino to play use the dial to adjust the car s speed going faster to gain more points based on the feedback on the lcd screen once the light turns yellow turn the dial so that the car stops moving before the red light appears after running three red lights the game is over and the high score is recorded | os |
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Embedded-System-Design-ELEN90066_2020_SM2- | embedded system design elen90066 2020 sm2 embedded system design elen90066 2020 sm2 | os |
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T.I.S | t i s technology information shop pershkrimi dyqani i cilesise ali express elektronik shqiptar aplikacioni do te jete ne 3 tri hapesira 1 faqja kryesore ku klienti mund te lundroj per te pare produktet me te fundit shoqeruar me oferten perkatese prezantuar nga kompania perkates 2 faqja e porosise ku do te shfaqen te gjitha porosite e bera nga klienti shoqeruar me informacionin perkates 3 faqja e perdoruesit ose profili i tij ku klienti ruan te dhenat e tij si emer mbiemer adresa numri i telefonit si dhe te dhenat bankare per te kryeer porosi ky aplikacion do te sherbej si nje perforcues i konkuruences midis kompanive elektronike per te paraqitur produktin e tyre me te mire shoqeruar me oferten klienti do te kete te drejte te zbuloj midis disa produkteve me te leverdishmin per te dhe te kryej porosi nga shtepia ky aplikacion eshte menduar te nis ne qytetin e vlores midis 3 tre kompanive elektronike qe operojne ne te si neptun globe aza electronic antaret e grupi hasan kolleshi kryetar grupi adriola ruko isjana salianji sidorela qosanj kristjana kociasi marjus aliaj category business updated not yet version 1 0 languages albanian english developer nav inc hasan kolleshi compatibility ios 11 or later android 7 0 win7 os x 10 9 linux size unknown | server |
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WebDevSrc | web development demos web development demo source files from marcofolio net http marcofolio net switch branches to get the different demos | front_end |
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KDD18-Gluon | kdd18 london deep learning and natural language processing with apache mxnet incubating gluon h3 time tuesday august 21 2018 br location icc capital suite room 14 15 16 h3 span style color grey presenter alex smola leonard lausen haibin lin span br abstract while deep learning has rapidly emerged as the dominant approach to training predictive models for large scale machine learning problems these algorithms push the limits of available hardware requiring specialized frameworks optimized for gpus and distributed cloud based training moreover especially in natural language processing nlp models contain a variety of moving parts character based encoders pre trained word embeddings long short term memory lstm cells and beam search for decoding sequential outputs among others this tutorial introduces gluonnlp http gluon nlp mxnet io github https github com dmlc gluon nlp a powerful new toolkit that combines mxnet s speed the user friendly gluon frontend and an extensive new library automating the most painful aspects of deep learning for nlp in this full day tutorial we will start off with a crash course on deep learning with gluon covering data autodiff and deep convolutional and recurrent neural networks then we ll dive into gluonnlp http gluon nlp mxnet io demonstrating how to work with word embeddings both pre trained and from scratch language models and the popular transformer model for machine translation preparation while most of the notebooks we prepared can run from the comfort of your laptop some more interesting real life problems benefit from more computation power at the tutorial we will provide each participant with a 50 aws credit code for you to try out these problems yourself on the amazon ec2 machines in preparation for the hands on tutorial please make sure that you have an aws account with at least one p2 8xlarge and one p3 2xlarge instance in eu ireland available for launch you may register an aws account and follow the instructions on this page https docs aws amazon com awsec2 latest userguide ec2 resource limits html to verify and request for p2 8xlarge and one p3 2xlarge instance limits in eu ireland region interested to learn more about gluonnlp https github com dmlc gluon nlp sign up https join slack com t apache mxnet shared invite enqtndiznjy0njq2njyylti1zgniogewotzkmzmyotg2zjnkowqynja5ngrhoti5ndy4mdy0nme1mdc2njezywq1mdzhnzu2nje5ytmyyta and join our slack channel https apache mxnet slack com messages cccdm10v9 we d love to hear from you have feedback to help us improve interested in career at amazonai contact us at amazonai kdd18 amazon com mailto amazonai kdd18 amazon com agenda time title slides notebooks 8 30 9 15 installation and basics ndarray autograd libraries link 1 link 00 link 01 9 15 9 30 neural networks 101 mlp convnet lstm loss sgd part i link 2 link 02 9 30 10 00 coffee break 10 00 10 30 neural networks 101 mlp convnet lstm loss sgd part ii link 02 10 30 11 00 computer vision 101 gluoncv link 3 link 03 11 00 11 30 parallel and distributed training link 4 link 04 11 30 12 00 data i o in nlp and iterators link 05 12 00 13 30 lunch break 13 30 14 15 embeddings link 5 link 06 14 15 15 00 language models lm link 5 link 07 15 00 15 30 sequence generation from lm link 6 link 08 15 30 16 00 coffee break 16 00 16 15 sentiment analysis link 09 16 15 17 00 transformer models and machine translation link 7 link 10 17 00 17 30 questions 1 https github com szha kdd18 gluon blob master slides kdd 20tutorial 201 pdf 2 https github com szha kdd18 gluon blob master slides kdd 20tutorial 202 pdf 3 https github com szha kdd18 gluon blob master slides kdd 20tutorial 203 pdf 4 https github com szha kdd18 gluon blob master slides kdd 20tutorial 204 pdf 5 https github com szha kdd18 gluon blob master slides kdd 20tutorial 205 pdf 6 https github com szha kdd18 gluon blob master slides kdd 20tutorial 206 pdf 7 https github com szha kdd18 gluon blob master slides kdd 20tutorial 207 pdf 00 https github com szha kdd18 gluon tree master 00 setup 01 https github com szha kdd18 gluon tree master 01 basics 02 https github com szha kdd18 gluon tree master 02 neural networks 03 https github com szha kdd18 gluon tree master 03 computer vision 04 https github com szha kdd18 gluon tree master 04 distributed training 05 https github com szha kdd18 gluon tree master 05 data pipeline 06 https github com szha kdd18 gluon tree master 06 word embedding 07 https github com szha kdd18 gluon tree master 07 language model 08 https github com szha kdd18 gluon tree master 08 sequence generation 09 https github com szha kdd18 gluon tree master 09 sentiment analysis 10 https github com szha kdd18 gluon tree master 10 translation | ai |
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ros2learn | a href http www acutronicrobotics com img src https github com acutronicrobotics gym gazebo2 blob dashing imgs alr logo png align left width 190 a this repository contains a number of ros and ros 2 enabled artificial intelligence ai and reinforcement learning rl algorithms algorithms that run in selected environments environments the repository contains the following algorithms algorithms techniques used for training and teaching robots environments environments pre built environments of interest to train selected robots experiments experiments experiments and examples of the different utilities that this repository provides a whitepaper about this work is available at https arxiv org abs 1903 06282 please use the following bibtex entry to cite our work misc 1903 06282 author yue leire erro nuin and nestor gonzalez lopez and elias barba moral and lander usategui san juan and alejandro solano rueda and v ctor mayoral vilches and risto kojcev title ros2learn a reinforcement learning framework for ros 2 year 2019 eprint arxiv 1903 06282 installation please refer to install md install md to install from sources refer to docker readme md docker readme md for ros2learn docker container installation and usage instructions usage tune hyperparameters check the optimal network hyperparameters for the environment you want to train hyperparams md hyperparams md train an agent you will find all available examples at experiments examples although the algorithms are complex the way to execute them is really simple for instance if you want to train mara robot using ppo2 mlp you should execute the following command sh cd ros2learn experiments examples mara python3 train ppo2 mlp py note that you can add the command line arguments provided by the environment which in this case are provided by the gym gazebo2 env use h to get all the available commands if you want to test your own trained neural networks or train with different environment form gym gazebo2 or play with the hyperparameters you must update the values of the dictionary directly in the corresponding algorithm itself for this example we are using ppo2 mlp from baselines https github com acutronicrobotics ros2learn tree dashing algorithms submodule so you can edit the mara mlp function inside baselines ppo2 defaults py https github com acutronicrobotics baselines blob 8396ea2dc4d19cabb7478f6c3df0119660f0ab18 baselines ppo2 defaults py l28 l53 example train https github com acutronicrobotics gym gazebo2 blob dashing imgs example train gif run a trained policy once you are done with the training or if you want to test some specific checkpoint of it you can run that using one of the running scripts available this time to follow with the example we are going to run a saved ppo2 mlp policy first we will edit the already mentioned mara mlp dictionary in particular the trained path value in baselines ppo2 defaults py https github com acutronicrobotics baselines blob 8396ea2dc4d19cabb7478f6c3df0119660f0ab18 baselines ppo2 defaults py l53 to the checkpoint we want checkpoints placed by default in tmp ros2learn now we are ready to launch the script since we want to visualize it in real conditions we are also going to set some flags sh cd ros2learn experiments examples mara python3 run ppo2 mlp py g r v 0 3 this will launch the simulation with the visual interface real time physics no speed up and 0 3 rad sec velocity in each servomotor example run https github com acutronicrobotics gym gazebo2 blob dashing imgs example run gif visualize training data on tensorboard the logdir path will change according to the used environment id and the used algorithm in training now you just have to execute tensorboard and open the link it will provide or localhost port number in your web browser you will find many useful graphs like the reward eprewmean plotted there you can also set a specific port number in case you want to visualize more than one tensorboard file from different paths sh tensorboard logdir tmp ros2learn maracollision v0 ppo2 mlp port 8008 example tensorboard https github com acutronicrobotics gym gazebo2 blob dashing imgs example tensorboard gif do your own experiment hyperparameter tunning existing environment 1 set the desired target in the corresponding environment in gym gazebo2 https github com acutronicrobotics ros2learn tree dashing environments submodule self target position self target orientation 2 set the desired hyperparameters in the corresponding default script of the algorithm in baselines https github com acutronicrobotics ros2learn tree dashing algorithms submodule create your own train script to use your own environment 1 create a session 2 get the hyperparameters from the corresponding defaults script of the algorithm to be used you will need to add a new dictionary for your own environment 3 make the environment dummyvecenv for a single instance subprocvecenv for multiple instances 4 call the corresponding learn function of the algorithm to be used optional save the statistics and checkpoints in tensorboard checkpoints tensorboard log monitor progress save the used hyperparameters in the training warning be aware of env set episode size episode size function if it is not called once the environment is made the default size of the episode will be 1024 it is advisable to set the same value as the one to be used in the learning algorithm or at least a power of 2 create your own run script to use your own environment 1 create a session 2 get the hyperparameters from the corresponding defaults script of the algorithm in baselines https github com acutronicrobotics ros2learn tree dashing algorithms submodule used in training time and also the target in your own environment self target position self target orientation 3 make a single environment dummyvecenv 4 normalize the environment vecnormalize if you have normalized in the training 5 make the model and load the checkpoint you want to test 6 get the actions from the model stochastic deterministic 7 execute the actions optional save in files some useful information such us accuracy position error axes orientation error quaternion | ros ros2 machine-learning ml reinforcement-learning rl ppo trpo dqn deep-learning robotics acktr | ai |
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