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demo-updated-moj-template-project | this demo is now archived the responsibility of the template is now within the cp team this repository is for prototyping upgrades of the gov uk prototype kit v12 1 0 and npm dependency updates before applying them to the moj prototype template repository this site is live on the cloud platform see the top right for the link it will display a snapshot of the makerecall prototype application this is used as reference only to test an application against the updates moj prototype kit template repo standards badge https img shields io badge dynamic json color blue style for the badge logo github label moj 20compliant query 24 data 5b 3f 28 40 name 20 3d 3d 20 22moj prototype template 22 29 5d status url https 3a 2f 2foperations engineering reports cloud platform service justice gov uk 2fgithub repositories https operations engineering reports cloud platform service justice gov uk github repositories moj prototype template link to report create a gov uk prototype kit website hosted on the moj cloud platform in addition to the protype kit v12 1 0 this repository contains cloud platform related files to run the website files to build a docker image to run the prototype site dockerfile dockerignore start sh a continuous deployment cd workflow targeting the cloud platform github workflows cd yaml kubernetes service tpl kubernetes ingress tpl kubernetes deployment tpl local development run the command npm start and open http localhost 3000 in a web browser updating protype kit to update protype kit in this repository see the update guide https govuk prototype kit herokuapp com docs updating the kit usage this is a template repository it requires a namespace on the cloud platform and github actions secrets in the repository settings which enable the cd workflow this is achieved via the the cloud platform guide on how to publish prototypes on the web the cloud platform guide to publish prototypes on the web explains the steps to create an new namespace on the cloud platform environments repository that is used to get your version of the template repository onto cloud platform quickly and with the least technical effort from the user in step 2 is a link to the template files that the cloud platform automatically apply to your version of the template repository during their continuous deployment stage but in this template repository those files already exist therefore before step 3 delete the file github repo tf from the resources folder before creating a pr this prevents the cloud platform cd failing as it attempts to overwrite existing files which it is not permitted to do alternatively if you would like to use the cloud platform template files delete the files listed above from your version of the template repository and keep the github repo tf file the files from the template will be applied to your repository via the cloud platform for further information on the cloud platform see the cloud platform user guide or see the ask cloud platform slack channel ask cloud platform https mojdt slack com archives c57upmzly cloud platform user guide https user guide cloud platform service justice gov uk cloud platform user guide template files https github com ministryofjustice cloud platform terraform github prototype tree main templates cloud platform environments https github com ministryofjustice cloud platform environments publish prototypes on the web https user guide cloud platform service justice gov uk documentation getting started prototype kit html publish prototypes on the web gov uk prototype kit https govuk prototype kit herokuapp com docs moj cloud platform https user guide cloud platform service justice gov uk documentation concepts about the cloud platform html github actions secrets https docs github com en actions reference encrypted secrets | cloud |
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Python-for-NLP | python for natural language processing this is the repository for the natural language processing at asian institute of technology google slide lectures can be found in https drive google com drive folders 14x9 y awyspizflavrze2ngy2h bejj usp sharing credits i would also like to give huge credits to several githubs web resources that i have revised to create this https web stanford edu class cs224n http spacy pythonhumanities com http courses spacy com https github com kushalj001 pytorch question answering https github com dsksd deepnlp models pytorch https github com bentrevett https github com graykode nlp tutorial https huggingface co course https kikaben com https github com kipgparker soft prompt tuning https github com moein shariatnia openai clip other very useful stuffs to get you started in the excited area of nlp https github com keon awesome nlp collection of all nlp learning resources https github com sebastianruder nlp progress omg this is like a mini wikipedia for nlp https github com mhagiwara 100 nlp papers listed first 100 influential nlp papers https captum ai tutorials good for working on explanable ai i would also like to thank students who have contributed amanda raj shrestha email st122245 ait ac th pranisaa charnparttarvanit email st121720 ait ac th chanapa pananookooln email st121395 ait ac th outline code tutorials covering each lab is 3 hours 1 fundamentals word vectors word2vec naive word vectors word2vec negative sampling word vectors glove window based name entity recognition dependency parsing 2 nlp spacy 3 dl classification generation case studies qa language modeling summarization pruning contrastive learning 4 huggingface introduction to huggingface case studies on summarization question answering soft prompt etc | machine-learning natural-language-processing nlp deep-learning | ai |
mtgjson-website | markdownlint disable next line div align center mtgjson documentation application img src docs public images assets logo mtgjson svg height 100px br br actions status https github com mtgjson mtgjson website workflows node 20ci badge svg https github com mtgjson mtgjson website actions codeql https github com mtgjson mtgjson website workflows codeql badge svg codecov https codecov io gh mtgjson mtgjson website branch main graph badge svg https codecov io gh mtgjson mtgjson website paypal https img shields io static v1 svg label paypal message support 20mtgjson color blue logo paypal https paypal me zachhalpern patreon https img shields io static v1 svg label patreon message support 20mtgjson color orange logo patreon https patreon com mtgjson mit license https img shields io badge license mit blue svg https github com mtgjson mtgjson website blob master license div getting started installation install node with brew https brew sh brew install n sudo n 16 16 developing runs the local build server with hot module reloading and eslint watcher npm run dev linting manually lint the files for any breaking changes npm run lint testing run all tests npm run test run all tests and a test build npm run test full building build out the entire site as a static project note this is done via the github action and pushed to a release tag so no need to do this unless you are testing the actual build additionally when submitting a pr netlify will deploy an environment for you to test your pull request npm run build purging clean out all node packages and vitepress cache npm run purge you can also just purge the vitepress cache with the following npm run purge cache | node vue vitepress | front_end |
charthub.litmuschaos.io | litmus chaos community chart hub fossa status https app fossa com api projects git 2bgithub com 2flitmuschaos 2fcharthub litmuschaos io svg type shield https app fossa com projects git 2bgithub com 2flitmuschaos 2fcharthub litmuschaos io ref badge shield development setup prerequisite golang is installed and configured if not follow the instructions here https golang org doc install install node js and npm follow the instructions here https nodejs org en download current repo should be cloned to your go path repo path should be gopath src github com litmuschaos charthub litmuschaos io tech stack from frontend x material ui https github com mui org material ui x typescript https www typescriptlang org x react https facebook github io react x redux https github com reactjs redux x redux thunk https github com gaearon redux thunk x redux persist https github com rt2zz redux persist x react router https github com reacttraining react router x redux devtools extension https github com zalmoxisus redux devtools extension x pwa support tech stack from backend x go https golang org dl x gorilla mux https github com gorilla mux x logrus https github com sirupsen logrus x gopkg in yaml v3 https gopkg in yaml v3 x gopkg in src d go git v4 https gopkg in src d go git v4 start frontend install it and run bash cd app client npm i npm start build it and serve bash cd app client npm run build npm install g serve serve s build enable pwa serviceworker optional just comment in the following line in the index tsx javascript registerserviceworker to javascript registerserviceworker start backend server bash cd app server go run main go the backend go server will be up and running on port 8080 dev setup enable prettier optional 1 step install the prettier plugin e g the one of esben petersen 2 add the following snippet to your settings in vscode json editor formatonsave true editor codeactionsonsave source organizeimports true optional usage open your browser and go to http localhost 3000 to access the frontend docker setup this project has been configured to run with docker you can initialize the system by running bash docker compose up this will setup the nginx and go server for you to access the frontend use http localhost you need to have docker and docker compose installed to use this method resources our standup open community meeting link feel free to drop by and participate in our discussion of new open source projects here https us02web zoom us j 89804064103 pwd cjjnwkvuee56suo2zwxvcjr2qwpcqt09 figma design document for the front end website view review give feedbacks and add comments suggests upgrades just about anything related to design right here https www figma com file cckf2ktcd7yx3gn4kwp9sc listmus chathub node id 0 3a1 visit our main litmus repo were are more than welcoming to a new contributor pay a visit and star it for updates right here https github com litmuschaos litmus license fossa status https app fossa com api projects git 2bgithub com 2flitmuschaos 2fcharthub litmuschaos io svg type large https app fossa com projects git 2bgithub com 2flitmuschaos 2fcharthub litmuschaos io ref badge large | typescript redux react reactjs | front_end |
Text-Generation-Webui-Podman | text generation webui podman docker this repository puts oobabooga text generation webui https github com oobabooga text generation webui into a container for full usage information see the readme md in that repository and the wiki https github com oobabooga text generation webui wiki this containerfile automatically builds gptq for llama so you can use 4bit llama models prerequisites a working install of nvidia container runtime for fedora see how to enable nvidia gpus in containers on bare metal in rhel 8 https www redhat com en blog how use gpus containers bare metal rhel 8 a working install of podman or docker a working install of podman compose or docker compose plugin podman usage podman compose build to pull the latest commit and build podman compose up to run the container by default on port 7861 docker usage docker sh will convert the containerfile into a valid dockerfile by removing some selinux labels see that file for more details docker compose f podman compose yaml build will pull the latest commit and build using the new modified dockerfile from the last step docker compose f podman compose yaml up will run the container gotchas you will also likely need to set the default runtime create the following file cat etc docker daemon json json runtimes nvidia path nvidia container runtime runtimeargs default runtime nvidia additionally if your machine is using selinux you may need to run in privileged by setting privileged true in the podman compose yaml file this may have security ramifications beyond the scope of this setup if you use selinux i highly suggest running rootless with podman instead data data and output will automatically be populated with files and directories from text generation webui files are set to copy once then never copy again if they exist if your models are on a different drive altogether you can still add additional mount points like so yaml volumes data data z output output z media some drive llama hfv2 data models z notes the command line arguments can be changed by modifying cli args in the podman compose yaml file license the license in this repository only applies to the files here not the original work at oobabooga text generation webui https github com oobabooga text generation webui with that said copyright 2023 aj walter git awalter net this work is free you can redistribute it and or modify it under the terms of the do what the fuck you want to public license version 2 as published by sam hocevar see the license file for more details | ai |
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IME-Inventory-Database | ime inventory database technical instructions tech stack frontend javascript es6 css html jinja template language mainly to work with flask backend flask pymongo database mongodb files ime inventory database dockerfile docker config file readme md development env development environment modify this in production docker compose yml docker compose config file requirements txt test data readme categories json categories used to sort test equipments load json shell script to purge the database and repopulate with pristine test data mongo postprocessing js pnf scraper ipynb python script to scrape test data from pnf website test data v3 json test data scrapedfrom pnf website web init py application factory where everthing starts config py load the env file and put them in the flask application db py database operations edit py process input and output for the equipment editing page search py search and front page logic static assets images and icons css all the style sheets js all the frontend logics user uploads obsolete templates jinja html templates user py serves user page utils py helper functions deploy on aws aws account pme developer at gmail com password see email recommended hosting environment aws lightsail amazon linux 2 3 5 month deployment git pull luanch through docker compose up build be sure to update development configuration in development env if used for production questions about code repo maintainance email me at zhenfengqiu at gmail com todos as of jun 10 2021 responsive mobile ui currently the ui breaks down on smaller screens add some media conditions in the css files to fix it user information editing page allow users to edit their information on their user page email confirmation system setup an email for the site so that users can get email confirmation when registaring accounts i would imagine this involves getting a domain name first although if there might be a way to make do with gmail api password retrieval allow user to change password it will probably involve working with the site email system as well hosting options hostname currently the demo is hosted on my private server since free trial on aws has expired follow the hosting option above to set up a new server environment then contact the school it staff to discuss hostname options regarding aws from my discussion with them hosting on aws seems to make integration into the school s system easier but docker compose is pretty versatile and we are already using a complete virtual environemnt so integration should be possible whereever you host your development server institution sign in integrate uchicago s shibboleth sign in system so users can sign in using their uchicago account this likely involves a lot of dicussion with the it staff and a lot of system design choices i would start with understanding the current database scheme and see if we can use some kind of common identifier to link uchicago account with our current user scheme but if you feel like scraping the whole thing thats fine too bulk upload this is a requested feature from the early feedbacks we gathered this will probably lead to big changes from database to the frontend template again a lot of work but certainly possible refactor frontend in react optional in retrospect react seems to be a fairly reasonable choice for our frontend framework the downside is that you can no longer use jinja with flask and frontend can only pass json data to and from backend so you will need a lot of async calls however using react will simplify a lot of the interactive logics that have became messier as features began to pile if you are considering refactoring and practice your framework skill maybe start with the equipment editing page since there are relatively less data exchanges | flask mongodb es6 | server |
cloud-engineering | cloud engineering collection of notes on cloud engineering | cloud |
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qcloud-iot-sdk-for-stm32withfreeRTOS-example | qcloud iot sdk for stm32withfreertos example qcloud iot sdk for stm32withfreertos example c sdk https github com tencentyun qcloud iot sdk embedded c git stm32mcu freertos sdk https i imgur com tnooacv png doc drivers stm32 f1xx hal inc mdk arm keil src middlewares sdk third party qcloud iot sdk embedded c qcloud iot sdk embedded c src platform sdk third party qcloud iot sdk embedded c samples third party qcloud iot sdk embedded c scenarized exhibitor shadow sample c readme md mit license sdk sdk c sdk https cloud tencent com document product 634 wiki https github com tencentyun qcloud iot sdk embedded c wiki | os |
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IOT-Espressif-Android-APK | iot espressif android apk iot espressif android released apks app app v1 0 0 mesh v1 1 0 v1 1 4 mesh v1 0 5 v1 0 9 app v1 1 0 mesh v1 1 0 v1 1 4 mesh v1 0 5 v1 0 9 app v1 1 1 mesh v1 1 0 v1 1 4 mesh v1 0 5 v1 0 9 app v1 1 2 mesh v1 1 0 v1 1 4 mesh v1 0 5 v1 0 9 app v1 1 3 mesh v1 1 0 v1 1 4 mesh v1 0 5 v1 0 9 app v1 1 4 mesh v1 1 0 v1 1 4 mesh v1 0 5 v1 0 9 app v1 1 5 mesh v1 1 0 v1 1 4 mesh v1 0 5 v1 0 9 app v1 1 6 mesh v1 1 0 v1 1 4 mesh v1 0 5 v1 0 9 app v1 2 0 mesh v1 1 0 v1 3 9 1 mesh v1 0 5 v1 0 9 app v1 2 1 mesh v1 1 0 v1 3 9 1 mesh v1 0 5 v1 0 9 app v1 2 2 mesh v1 1 0 v1 3 9 1 mesh v1 0 5 v1 0 9 app v1 2 3 mesh v1 1 0 v1 3 9 1 mesh v1 0 5 v1 0 9 app v1 2 4 mesh v1 1 0 v1 3 9 1 mesh v1 0 5 v1 0 9 app v1 2 5 mesh v1 1 0 v1 3 9 1 mesh v1 0 5 v1 0 9 1 v1 3 0 v1 3 0 light v1 3 0 v1 3 0 light | server |
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awesome-zephyr-rtos | dark logo assets awesome zephyr rtos logo dark png gh dark mode only ligh logo assets awesome zephyr rtos logo light png gh light mode only awesome zephyr rtos awesome https awesome re badge svg https awesome re the zephyr rtos is based on a small footprint kernel designed for use on resource constrained and embedded systems from simple embedded environmental sensors and led wearables to sophisticated embedded controllers smart watches and iot wireless applications what is an awesome list https github com sindresorhus awesome blob main awesome md contents official resources official resources libraries libraries tools tools open source hardware open source hardware videos videos learning material learning material official resources zephyrproject org https www zephyrproject org official website docs zephyrproject org https docs zephyrproject org project documentation github https github com zephyrproject rtos project github organization zephyr https github com zephyrproject rtos zephyr main repo west https github com zephyrproject rtos west swiss army knife command line tool sdk ng https github com zephyrproject rtos sdk ng next generation toolchains host tools example application https github com zephyrproject rtos example application example out of tree application that is also a module docker image https github com zephyrproject rtos docker image docker image suitable for development and ci discord https discord com invite ck7jw53nu2 community chat hosted on discord mailing list https lists zephyrproject org g main subgroups mail web based mailing list powere by groups io youtube https www youtube com c zephyrproject conferences videos and event highlights blog https www zephyrproject org community blog rss https www zephyrproject org category blog feed posts from the project and community twitter https twitter com zephyriot linkedin https www linkedin com company the zephyr project facebook https www facebook com zephyriot various social feeds newsletter https www zephyrproject org newsletter quarterly newsletter ambassadors https www zephyrproject org ambassadors list of community experts vulnerability alert registry https www zephyrproject org vulnerability registry email notifications of vulnerabilties store https zephyr project myspreadshop com get merch job board https www zephyrproject org careers search roles from zephyr member companies libraries application frameworks gsoc 2022 arduino core https github com zephyrproject rtos gsoc 2022 arduino core arduino core api module with an arduino c style abtraction layer chre https github com zephyrproject rtos chre context hub runtime environment chre is android s platform for developing always on applications called nanoapps control https github com swedishembedded control a control systems design library written in pure c that provides you with advanced algorithms for control state estimation and model identification specifically designed for use on embedded systems micro ros zephyr module https github com micro ros micro ros zephyr module ros 2 for microcontrollers open amp https github com zephyrproject rtos open amp open asymmetric multi processing openamp framework sense vm https github com svenssonjoel sense vm bytecode virtual machine for microcontrollers swedish embedded platform sdk https github com swedishembedded sdk swedish embedded platform sdk is a comprehensive platform for firmware development wasm micro runtime https github com bytecodealliance wasm micro runtime lightweight standalone webassembly wasm runtime zpp https github com lowlander zpp c 20 framework filesystem fats https github com zephyrproject rtos fatfs generic fat exfat filesystem module for small embedded systems littlefs https github com zephyrproject rtos littlefs little fail safe filesystem designed for microcontrollers nffs https github com zephyrproject rtos nffs flash file system prioritizing minimal ram usage reliability hal pal cmsis https github com zephyrproject rtos cmsis standardized api for the cortex m processor core and peripherals libmetal https github com zephyrproject rtos libmetal abstraction layer across user space linux baremetal and rtos environments iot cloud anjay zephyr https github com avsystem anjay zephyr c implementation of the client side oma lwm2m protocol edge impulse https github com edgeimpulse example standalone inferencing zephyr machine learning on edge devices golioth https github com golioth golioth zephyr sdk device management cloud enablement platform memfault https github com memfault memfault firmware sdk tree master ports zephyr cloud based debugging observability openhaystack zephyr https github com koenvervloesem openhaystack zephyr track personal bluetooth devices via apple s massive find my network send my sensor https github com koenvervloesem send my sensor upload sensor data from a device without internet connection by ab using apple s find my network thingset zephyr sdk https github com thingset thingset zephyr sdk a software development kit sdk based on zephyr rtos to integrate communication interfaces using the thingset protocol into an application with minimum effort see https thingset io networking protocols bacnet stack https github com bacnet stack bacnet stack bacnet open source protocol stack for embedded systems linux and windows canopennode https github com zephyrproject rtos canopennode canopen stack civetweb https github com zephyrproject rtos civetweb embeddable web server cbor https cbor io concise binary object representation tinycbor https github com zephyrproject rtos tinycbor small cbor library qcbor https github com laurencelundblade qcbor comprehensive cbor library zcbor https github com nordicsemiconductor zcbor cbor library that includes support for cddl cosy https github com lindemer cozy cbor object signing and encryption cose greybus for zephyr https github com cfriedt greybus for zephyr protocol for hotpluggable devices nanopb https github com zephyrproject rtos nanopb protocol buffers for embedded systems openthread https github com zephyrproject rtos openthread thread mesh networking protocol pjon https github com gioblu pjon multi master multi media network protocol s2opc https gitlab com systerel s2opc open source opc ua toolkit designed with security and embedded devices in mind security aerology https github com linaro aerology inspect zephyr and tf m applications post mortem mbed tls https github com zephyrproject rtos mbedtls c library that implements cryptographic primitives x 509 certificate manipulation and the ssl tls and dtls protocols mcuboot https github com zephyrproject rtos mcuboot a secure bootloader for 32 bits microcontrollers tf m https github com zephyrproject rtos trusted firmware m platform security architecture psa for armv7 m and armv8 m tinycrypt https github com zephyrproject rtos tinycrypt cryptographic library with a minimal set of standard cryptography primitives misc ecfw zephyr https github com intel ecfw zephyr embedded controller for low level tasks on a motherboard like power sequencing grbl https github com iwasz zephyr grbl motion control for cnc milling lvgl https github com zephyrproject rtos lvgl complete graphics library lz4 https github com zephyrproject rtos lz4 extremely fast compression algorithm pinetime zephyr https github com najnesnaj pinetime zephyr smartwatch operating system zephyr rust https github com tylerwhall zephyr rust api bindings libstd and cargo integration for rust linaro sensor pipeline https github com microbuilder linaro sensor pipeline secure data pipelines pysvd2dts https github com thedigitaledge pysvd2dts creates a zephyr devicetree file from an arm cmsis svd file sof https github com zephyrproject rtos sof audio digital signal processing dsp firmware infrastructure and sdk spinner https github com teslabs spinner motor control firmware based on the field oriented control foc principles tflite micro https github com zephyrproject rtos tflite micro tensorflow lite for microcontrollers zbus https github com zephyr bus zbus inter thread communication bus zscilib https github com zephyrproject rtos zscilib scientific computing library zcalendar https github com bpbradley zcalendar calendar api with rtc integration zmk https github com zmkfirmware zmk keyboard firmware with a rich featureset and broad hardware support tools build config bazel2zephyr https github com gatcode bazel2zephyr embedded bare metal development using bazel cmake device tree dtsh https github com dottspina dtsh shell like interface to devicetrees kconfig make ninja swedish embedded platform sdk docker image https github com swedishembedded develop docker containers for ci development compilers note the official sdk includes several compilers gnu arm embedded arm compiler 6 intel oneapi toolkit designware arc metaware development toolkit mwdt cadence tensilica xtensa c c compiler xcc espressif tools editors ides visual studio code ardesco vscode extension https github com ericsson ardesco vscode extension ericsson ardesco device development extension zephyr tools for vscode https github com circuitdojo zephyr tools circuit dojo designed zephyr tools to make getting started with zephyr a snap embedded tools https marketplace visualstudio com items itemname ms vscode vscode embedded tools a register viewer for cmsis svd files and an rtos data viewer nrf connect for vs code https marketplace visualstudio com items itemname nordic semiconductor nrf connect platformio https docs zephyrproject org latest guides platformio index html vs code importer https github com smrtos zephyr2vsc zephyrus https github com tuscale vscode zephyrus other editors ides eclipse https github com zephyrproject rtos eclipse plugin cmake zephyr helpers https github com thirdpin zephyr cmake helpers enhance cmake automation for use with vs code flash debug test aerology https github com linaro aerology inspect zephyr and tf m applications post mortem atmel sam ba edtt embedded device test tool https github com zephyrproject rtos edtt esptool gnu tools gdb binutils https github com zephyrproject rtos binutils gdb mcumgr https github com zephyrproject rtos mcumgr android https github com nordicsemiconductor android nrf connect device manager ios https github com nordicsemiconductor ios nrf connect device manager web https github com boogie mcumgr web openocd https github com zephyrproject rtos openocd pyocd segger https github com zephyrproject rtos segger j link https github com zephyrproject rtos libjaylink twister simulation acrn qemu https github com zephyrproject rtos qemu network tools https github com zephyrproject rtos net tools seabios https github com zephyrproject rtos seabios renode https zephyr dashboard renode io xen version control zephyr pre commit hooks https github com cgnd zephyr pre commit hooks a collection of pre commit https pre commit com hooks for use with zephyr open source hardware zswatch https github com jakkra zswatch the open source zephyr based smartwatch including both hw and fw videos zephyr developer summit june 2021 https www youtube com playlist list plzrqulb6 ipg39tvb dekioss5wqlbk6i embedded linux conference open source summit sept 2021 https www youtube com playlist list plzrqulb6 ipefltsxvm0xbuu84b8 sum7 zephyr videos from golioth https www youtube com playlist list plxgira7qd83dljhi7f3euggsf4hbvhonp zephyrrtos https www youtube com hashtag zephyrrtos videos tagged with zephyrrtos learning material tutorial for beginners https github com maksimdrachov zephyr rtos tutorial nordic developer academy https www nordicsemi com support nordic developer academy ultimate embedded firmware devops infrastructure https www udemy com course ultimate embedded firmware devops infrastructure contribute contributions welcome read the contribution guidelines contributing md first | zephyr zephyr-rtos iot real-time microcontroller embedded mcu rtos lists awesome awesome-list | os 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TestApplication | testapplication mobile development | front_end |
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ml-training-intro | introduction to machine learning with andreas mueller instructor andreas mueller http amuller github io amuellerml https twitter com amuellerml columbia university book introduction to machine learning with python http shop oreilly com product 0636920030515 do this repository will contain the teaching material and other info associated with the introduction to machine learning course content introduction to ml https amueller github io ml training intro slides 00 introduction html supervised learning https amueller github io ml training intro slides 01 supervised learning html unsupervised learning https amueller github io ml training intro slides 02 unsupervised learning html cross validation and grid search https amueller github io ml training intro slides 03 cross validation grid search html preprocessing https amueller github io ml training intro slides 04 preprocessing html linear models for regression https amueller github io ml training intro slides 05 linear models regression html linear models for classification https amueller github io ml training intro slides 06 linear models classification html trees and forests https amueller github io ml training intro slides 07 trees forests html gradient boosted trees https amueller github io ml training intro slides 08 gradient boosting html obtaining the tutorial material if you are familiar with git it is probably most convenient if you clone the github repository this is highly encouraged as it allows you to easily synchronize any changes to the material git clone https github com amueller ml training intro git if you are not familiar with git you can download the repository as a zip file by heading over to the github repository https github com amueller ml training intro in your browser and click the green download button in the upper right images download repo png please note that i may add and improve the material until shortly before the tutorial session and we recommend you to update your copy of the materials one day before the tutorials if you have an github account and forked cloned the repository via github you can sync your existing fork with via the following commands git pull origin master installation notes this tutorial will require recent installations of numpy http www numpy org scipy http www scipy org matplotlib http matplotlib org pillow https python pillow org pandas http pandas pydata org scikit learn http scikit learn org stable 0 18 1 ipython http ipython readthedocs org en stable jupyter notebook http jupyter org the last one is important you should be able to type jupyter notebook in your terminal window and see the notebook panel load in your web browser try opening and running a notebook from the material to see check that it works for users who do not yet have these packages installed a relatively painless way to install all the requirements is to use a python distribution such as anaconda https www continuum io downloads which includes the most relevant python packages for science math engineering and data analysis anaconda can be downloaded and installed for free including commercial use and redistribution the code examples in this tutorial should be compatible to python 2 7 python 3 4 and later however it s recommended to use a recent python version like 3 5 or 3 6 after obtaining the material we strongly recommend you to open and execute a jupyter notebook jupter notebook check env ipynb that is located at the top level of this repository inside the repository you can open the notebook by executing bash jupyter notebook check env ipynb inside this repository inside the notebook you can run the code cell by clicking on the run cells button as illustrated in the figure below images check env 1 png finally if your environment satisfies the requirements for the tutorials the executed code cell will produce an output message as shown below images check env 2 png | ai |
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dgm4nlp | dgm4nlp deep generative models for natural language processing | ai |
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Web-Development-with-Angular-2-and-Bootstrap | angular 2 development with typescript alt tag https www packtpub com sites default files bookretailers 9781785889646 jpg web development with angular 2 and bootstrap https www packtpub com web development web development angular 2 and bootstrap video chapter 1 introduction to angular 2 1 course overview introduction and objective of course and application overview 2 angular 2 0 vs angular 1 0 3 installation and setup for angular 2 0 with typescript es6 4 let s start create first hello world application angular 2 0 chapter 2 getting started with angular 2 1 bootstrap styles sass and javascript installation and setup for application 2 bootstrap fluid responsive layout with grid system 3 bootstrap responsive nav navbar header 4 bootstrap table list form and glyph icons responsive utilities 5 bootstrap carousel with bootstrap panel accordion tab menu 6 creating demo application structure using bootstrap component chapter 3 module bundler transpilers 1 writing application using typescript ecmascript 5 ecmascript 6 2 typescript as a language for angular applications 3 understanding universal module loader system js 4 understanding module bundler web pack 5 angular 2 0 different loaders and transpilers using npm package managers 6 typescript annotations for components views directives 7 hands on getting started with application chapter 4 angular 2 0 es6 features 1 scope of variables let const understanding different template view and directives 2 template literals optional parameters with default values 3 spread operator rest parameter and de structuring 4 arrow function expressions and lexical scope binding 5 iterators generators with for each for in and for of 6 classes and inheritance 7 asynchronous processing with promises 8 modules import exports chapter 5 angular 2 components modules 1 angular 2 components modules 2 angular 2 modular development using ngmodule 3 angular 2 0 dom shadow view encapsulation 4 angular 2 app architecture 5 component nesting templates 6 angular component metadata 7 component communication with input and output 8 application development with data binding pipes chapter 6 angular 2 0 components communication 1 data binding and property binding 2 dom events and event binding 3 two way data binding 4 attribute directives and structural directives 5 pipes 6 angular 2 application lifecycle hooks 7 application development with data binding pipes directives in angular 2 chapter 7 dependency injection in angular 2 1 the dependency injection and inversion of control patterns 2 injectors and providers 3 building a service registering service 4 injecting the service 5 dependency injection with angular 2 application chapter 8 routing with angular 2 1 angular2 0 understanding routing basics 2 angular 2 0 passing data to routes 3 child routes auxiliary routes 4 lazy loading with asyncroute 5 hands on using routing in our application chapter 9 forms in angular 2 1 introducing to angular 20 forms 2 form controls form directives in template driven forms 3 template driven forms with validation 4 model driven forms or reactive forms with custom validation 5 angular 2 0 application development with angular forms chapter 10 reactive programming in angular 2 0 1 introduction of reactive programming 2 observables and reactive extensions 3 setting up http service with rx js 4 sending an http request 5 subscribing to an observable 6 adding http service in application | front_end |
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illustrated-machine-learning.github.io | p align center img src public img banner png p welcome to our website where we strive to make the complex world of machine learning more approachable through clear and concise illustrations our goal is to provide a visual aid for students professionals and anyone preparing for a technical interview to better understand the underlying concepts of machine learning whether you re just starting out in the field or you re a seasoned professional looking to refresh your knowledge we hope our illustrations will be a valuable resource on your journey to understanding machine learning we re all humans therefore if you find any mistake please raise an issue and let us know if you are interested to help us with the development of our website please don t hesitate to reach out to us we welcome any and all offers of help p align center a href https illustrated machine learning github io illustrated machine learning github io a p | illustrations machine-learning ml-illustrations illustrated-machine-learning | ai |
Fabric.Cashmere | build status https dev azure com healthcatalyst cap apis build status healthcatalyst fabric cashmere branchname refs 2fpull 2f1701 2fmerge https dev azure com healthcatalyst cap build latest definitionid 2105 branchname refs 2fpull 2f1701 2fmerge cashmere banner https raw githubusercontent com healthcatalyst fabric cashmere master cashmerebanner png cashmere is health catalyst s comprehensive design system it includes an angular ui library with components and styles for health catalyst branded web applications a cashmere themed react library based on material ui components general styling standards colors branding iconography typography etc content development guidelines copywriting terminology definitions and a collection of user personas analytics development guidelines for qlik tableau and powerbi quick links releases https github com healthcatalyst fabric cashmere releases components http cashmere healthcatalyst net web components foundations http cashmere healthcatalyst net foundations content http cashmere healthcatalyst net content getting started http cashmere healthcatalyst net web guides getting started guidelines for contribution http cashmere healthcatalyst net web guides contribution guide submit an issue http cashmere healthcatalyst net web guides submit an issue supported browsers http cashmere healthcatalyst net web guides supported browsers installing to an existing project refer to the instructions in our getting started http cashmere healthcatalyst net web guides getting started guide running the demo application to run the cashmere demo site locally refer to the instructions in our guidelines for contribution http cashmere healthcatalyst net web guides contribution guide guide to setup your environment sponsors thanks to browserstack http www browserstack com for kindly providing the project with free of charge automatic testing time browserstack https raw githubusercontent com healthcatalyst fabric cashmere master browserstack logo 2x png | angular style-guide cashmere hacktoberfest | os |
EnterpriseData-with-LLM | enterprisedata with llm generative ai is creating lots of exciting use cases across industries to create true business value from generative ai requires integration of large language models llm with enterprise knowledge base llms are not trained on proprietary enterprise specific knowledge but are trained on publicly available internet data they might hallucinate and provide incorrect response to enterprise specific questions in this repository i will present a way to quickly within 1 2 hours and securely integrate your enterprise data confluence pages salesforce data crm data relational databases manuals etc with large language models llm this is a full end to end solution no model training fine tuning or extensive deployment needed you also do not need any specific ai ml experience or extensive developer knowledge to deploy this solution the answers provided will be grounded in your organisations specific knowledge avoiding factuality issues such as hallucinations and out of context responses this solution will enable enterprises to create a lot of business use cases like improving customer experience intelligent chat bots providing answers based on enterprise data say order status account balance etc increasing internal employee productivity by generating enterprise specific proposals marketing material manuals job descriptions etc internal search engine searching code repositories internal documents etc animatedimage https github com sachink2010 enterprisedata with llm assets 4855287 e6e83c11 478c 404c 8a86 4cdf0d11087e if you want to read more about architecture choices made here please read medium blog https medium com sachin kulkarni nl generative ai with enterprise data 3c81a8bffaf2 architecture of solution img width 935 alt image src https github com sachink2010 enterprisedata with llm assets 4855287 ba0fcfbc 67da 4781 840c a6afd8c3525a here are steps to implement this solution b 1 set up your aws sagemaker studio environment and git clone b login to your aws account select any region for e g ireland eu west 1 as the region and navigate to amazon sagemaker management console click on studio link in the left and then click on the open studio link img width 308 alt image src https github com sachink2010 enterprisedata with llm assets 4855287 77e94527 038b 4bb4 bdc0 eb769715335f it will launch amazon sagemaker studio in a new browser window or tab in the studio click on file in the top menu next open terminal in terminal tab you can type in git clone https github com sachink2010 enterprisedata with llm b 2 set up your kendra index b using aws console upload files in bank financial statements folder to your s3 folder create a kendra index add data source as s3 bucket set up sync as periodic based on your needs follow steps as shown in src createkendraindex folder b 3 run your streamlit app in sagemaker studio terminal and start using the app b set the kendra index id variable in the kendra rag streamlitapp py file to match the index you created in step 2 in sagemaker terminal window type streamlit run streamlit run enterprisedata with llm src streamlit kendra rag streamlitapp py server port 6006 you will see that streamlit app is running message in your terminal session img width 924 alt image src https github com sachink2010 enterprisedata with llm assets 4855287 7afd3d39 2a34 421b bdc1 ad6d08faeef8 copy your sagemaker domain id your region where sagemaker studio is running and streamlit port from previous step in a new same browser window in a new tab open link https studio id studio region sagemaker aws jupyter default proxy port for e g https d 1n8b7wqrjeyx studio eu west 1 sagemaker aws jupyter default proxy 6006 start using the app img width 833 alt image src https github com sachink2010 enterprisedata with llm assets 4855287 2f6d1c32 c865 438d a693 e36520086689 | ai |
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multilingual_detox | exploring cross lingual textual style transfer with large multilingual language models this repository contains code for the paper submitted to acl srw https sites google com view acl srw 2022 home exploring cross lingual textual style transfer with large multilingual language models by daniil moskovskiy mailto daniil moskovskiy skoltech ru daryna dementieva mailto daryna dementieva skoltech ru and alexander panchenko mailto a panchenko skoltech ru setup step 1 install dependencies pip install r requirements txt step 2 run experiments multilingual setup python mt5 trainer py batch size 16 use russian 1 max steps 40000 learning rate 1e 5 output dir trained models cross lingual setup python mt5 trainer py batch size 16 use russian 0 max steps 40000 learning rate 1e 5 output dir trained models step 3 generate detoxifications for test data for russian use test tsv file from data russian data for english use data english data test toxic parallel txt example for russian python inference py model name mbart model path mbarts mbart 10000 en ru language ru and for english python inference py model name mbart model path mbarts mbart 10000 en ru language en step 4 calculate metrics example for russian python evaluate ru py result filename results en input dir mbarts mbart 10000 en ru output dir mbarts data for english we use paradetox parallel detoxification corpora please cite the original paper https aclanthology org 2022 acl long 469 and proceed to the original paradetox repository https github com skoltech nlp paradetox for details for russian we use rudetox corpora from russe detoxification competition https russe nlpub org 2022 tox please cite the competition if you are going to use the data citation for english data inproceedings logacheva etal 2022 paradetox title p ara d etox detoxification with parallel data author logacheva varvara and dementieva daryna and ustyantsev sergey and moskovskiy daniil and dale david and krotova irina and semenov nikita and panchenko alexander booktitle proceedings of the 60th annual meeting of the association for computational linguistics volume 1 long papers month may year 2022 address dublin ireland publisher association for computational linguistics url https aclanthology org 2022 acl long 469 pages 6804 6818 abstract we present a novel pipeline for the collection of parallel data for the detoxification task we collect non toxic paraphrases for over 10 000 english toxic sentences we also show that this pipeline can be used to distill a large existing corpus of paraphrases to get toxic neutral sentence pairs we release two parallel corpora which can be used for the training of detoxification models to the best of our knowledge these are the first parallel datasets for this task we describe our pipeline in detail to make it fast to set up for a new language or domain thus contributing to faster and easier development of new parallel resources we train several detoxification models on the collected data and compare them with several baselines and state of the art unsupervised approaches we conduct both automatic and manual evaluations all models trained on parallel data outperform the state of the art unsupervised models by a large margin this suggests that our novel datasets can boost the performance of detoxification systems citation for russian data article russe2022detoxification title russe 2022 findings of the first russian detoxification task based on parallel corpora author dementieva daryna and nikishina irina and logacheva varvara and fenogenova alena and dale david and krotova irina and semenov nikita and shavrina tatiana and panchenko alexander booktitle computational linguistics and intellectual technologies year 2022 results main results are depicted in this table below p align center img width 460 height 300 src https github com skoltech nlp multilingual detox blob main pics main table png p https github com skoltech nlp multilingual detox blob main pics main table png here are some examples of generated text https github com skoltech nlp multilingual detox blob main pics generation png p align center img width 460 height 300 src https github com skoltech nlp multilingual detox blob main pics generation png p citation inproceedings dblp conf acl moskovskiydp22 author daniil moskovskiy and daryna dementieva and alexander panchenko editor samuel louvan and andrea madotto and brielen madureira title exploring cross lingual text detoxification with large multilingual language models booktitle proceedings of the 60th annual meeting of the association for computational linguistics student research workshop acl 2022 dublin ireland may 22 27 2022 pages 346 354 publisher association for computational linguistics year 2022 url https aclanthology org 2022 acl srw 26 timestamp thu 19 may 2022 16 52 59 0200 biburl https dblp org rec conf acl moskovskiydp22 bib bibsource dblp computer science bibliography https dblp org contacts if you find some issue do not hesitate to add it to github issues https github com skoltech nlp multilingual detox issues feel free to contact daniil moskovskiy via e mail mailto daniil moskovskiy skoltech ru or telegram t me etomoscow | ai |
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nlp_newsletter | nlp newsletter the nlp newsletter provides weekly or biweekly quick summaries of some of the latest natural language processing nlp and machine learning ml stories across a range of important categories such as fairness ethics society educational resources publications etc want your story or project to be featured in the nlp newsletter reach out via ellfae gmail com or twitter https twitter com omarsar0 if you are interested in translating any of the nlp newsletter issues you can check out this github issue https github com dair ai dair ai github io issues 11 subscribe https dair ai newsletter to the nlp newsletter to receive future issues in your inbox how to contribute you can check out our project page https github com orgs dair ai projects 8 to see all the ongoing tasks or issues related to this research project lookout for the main nlp newsletter tag issues with the good first issue tag are good tasks to get started with you can also just check the issues tab https github com dair ai nlp newsletter issues you can ask anything related to this project in our slack group https join slack com t dairai shared invite zt dv2dwzj7 f9ht047jigkunnkv88lq g slack channel nlp newsletter newsletter issue date translations nlp newsletter 13 acl highlights tabert texthero ml methods climbing towards nlu july 13 2020 english https dair ai nlp newsletter 13 en french https dair ai nlp newsletter 13 fr nlp newsletter 12 hateful memes textattack detr bleurt gamegan survey papers june 30 2020 english https dair ai nlp newsletter 12 en french https dair ai nlp newsletter 12 fr nlp newsletter 11 jukebox hybridqa tldr generation blender the sota chatbot torchserve ai economist wt5 may 4 2020 english https dair ai nlp newsletter 11 en turkish https dair ai nlp newsletter 11 tr french https dair ai nlp newsletter 11 fr nlp newsletter 10 improving reproducibility in ml privacy and security in nlp extreme longformer vilbert exbert april 19 2020 english https dair ai 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compositional generalization neural tangents mar 16 2020 english https dair ai nlp newsletter nlp 7 french https dair ai nlp newsletter 7 fr chinese https dair ai nlp newsletter nlp 7 zh md brazilian portuguese https dair ai nlp newsletter pt br nlp 7 nlp newsletter issue 6 bertology primer fastpages t5 data science education pytorch notebooks slow science in ml mar 02 2020 english https dair ai nlp newsletter bertology primer fastpages t5 french https dair ai nlp newsletter 6 fr brazilian portuguese pt br https dair ai nlp newsletter pt br bertology primer fastpages t5 chinese https dair ai nlp e7 ae 80 e6 8a a5 nlp newsletter issue 5 the annotated gpt 2 understanding self distillation haiku ganilla sparkwiki ethics in nlp torchmeta feb 23 2020 english https dair ai nlp newsletter the annotated gpt 2 understanding brazilian portuguese https dair ai nlp newsletter pt br the annotated gpt 2 understanding chinese https dair ai nlp e7 ae 80 e6 8a a5 issue 5 the annotated gpt 2 codebert jax ga french https dair ai nlp newsletter 5 fr spanish https dair ai bolet c3 adn informativo nlp gpt 2 explicado entendie arabic https dair ai nlp newsletter ar the annotated gpt 2 and more nlp newsletter issue 4 pytorch3d deepspeed turing nlg question answering benchmarks hydra sparse neural networks feb 16 2020 english https dair ai nlp newsletter pytorch3d deepspeed turing nlg chinese https dair ai nlp e7 ae 80 e6 8a a5 issue 4 pytorch3d deepspeed turing nlg brazilian portuguese https dair ai nlp newsletter pt br pytorch3d deepspeed turing nlg french https dair ai nlp newsletter 4 fr nlp newsletter issue 3 flax thinc language specific bert models meena flyte lasertagger feb 2 2020 english https dair ai nlp newsletter flax thinc language specific bert chinese https dair ai nlp e7 ae 80 e6 8a a5 flax thinc language specific bert models french https dair ai nlp newsletter 3 fr nlp newsletter issue 2 reformer deepmath electra tinybert for search vizseq open sourcing ml jan 19 2020 english https dair ai nlp newsletter reformer deepmath electra tinyb copy chinese https dair ai nlp e7 ae 80 e6 8a a5 reformer deepmath electra tinybert brazilian portuguese https dair ai nlp newsletter pt br reformer deepmath electra tinyb french https dair ai nlp newsletter 2 fr nlp newsletter issue 1 tokenizers tensorflow 2 1 textvectorization torchio nlp shortfalls jan 12 2020 english https dair ai nlp newsletter tokenizers tensorflow 2 1 textve chinese https dair ai nlp e7 ae 80 e6 8a a5 tokenizers tensorflow 2 1 textvectorization brazilian portuguese https dair ai nlp newsletter pt br tokenizers tensorflow 2 1 textve french https dair ai nlp newsletter 1 fr | nlp machine-learning deep-learning | ai |
growthschool_cloud_data_engineering | growth school cloud data engineering course growth school cloud data engineering course | cloud |
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ICOM4217-Embedded-System-Design | icom4217 embedded system design | os |
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Python-Natural-Language-Processing-Cookbook | python natural language processing cookbook a href https www packtpub com product python natural language processing cookbook 9781838987312 utm source github utm medium repository utm campaign 9781838987312 img src https static packt cdn com products 9781838987312 cover smaller alt python natural language processing cookbook height 256px align right a this is the code repository for python natural language processing cookbook https www packtpub com product python natural language processing cookbook 9781838987312 utm source github utm medium repository utm campaign 9781838987312 published by packt over 50 recipes to understand analyze and generate text for implementing language processing tasks what is this book about python is the most widely used language for natural language processing nlp thanks to its extensive tools and libraries for analyzing text and extracting computer usable data this book will take you through a range of techniques for text processing from basics such as parsing the parts of speech to complex topics such as topic modeling text classification and visualization starting with an overview of nlp the book presents recipes for dividing text into sentences stemming and lemmatization removing stopwords and parts of speech tagging to help you to prepare your data you ll then learn ways of extracting and representing grammatical information such as dependency parsing and anaphora resolution discover different ways of representing the semantics using bag of words tf idf word embeddings and bert and develop skills for text classification using keywords svms lstms and other techniques as you advance you ll also see how to extract information from text implement unsupervised and supervised techniques for topic modeling and perform topic modeling of short texts such as tweets additionally the book shows you how to develop chatbots using nltk and rasa and visualize text data by the end of this nlp book you ll have developed the skills to use a powerful set of tools for text processing this book covers the following exciting features become well versed with basic and advanced nlp techniques in python represent grammatical information in text using spacy and semantic information using bag of words tf idf and word embeddings perform text classification using different methods including svms and lstms explore different techniques for topic modeling such as k means lda nmf and bert work with visualization techniques such as ner and word clouds for different nlp tools build a basic chatbot using nltk and rasa extract information from text using regular expression techniques and statistical and deep learning tools if you feel this book is for you get your copy https www amazon com dp b08srdf78y today a href https www packtpub com utm source github utm medium banner utm campaign githubbanner img src https raw githubusercontent com packtpublishing github master github png alt https www packtpub com border 5 a instructions and navigations all of the code is organized into folders the code will look like the following def add ner to model nlp if ner not in nlp pipe names ner nlp create pipe ner nlp add pipe ner last true else ner nlp get pipe ner return nlp ner following is what you need for this book this book is for data scientists and professionals who want to learn how to work with text intermediate knowledge of python will help you to make the most out of this book if you are an nlp practitioner this book will serve as a code reference when working on your projects you will need python 3 installed on your system we recommend installing the python libraries discussed in this book using pip the code snippets in the book mention the relevant command to install a given library on the windows os with the following software and hardware list you can run all code files present in the book chapter 1 8 software and hardware list chapter software required os required 1 8 python 3 6 jupyter notebook anaconda windows mac os x and linux any before you run the code please make sure to 1 install all necessary packages see requirements txt 2 download all required models see text 3 run the files from the python natural language processing cookbook directory using commands similar to the following python m chapter01 po tagging we also provide a pdf file that has color images of the screenshots diagrams used in this book click here to download it https static packt cdn com downloads 9781838987312 colorimages pdf related products other books you may enjoy hands on python natural language processing packt https www packtpub com product hands on python natural language processing 9781838989590 amazon https www amazon com dp b08bg5581y getting started with google bert packt https www packtpub com product getting started with google bert 9781838821593 amazon https www amazon com dp 1838821597 get to know the author zhenya anti is a natural language processing nlp professional working at practical linguistics inc she helps businesses to improve processes and increase productivity by automating text processing zhenya holds a phd in linguistics from university of california berkeley and a bs in computer science from massachusetts institute of technology 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 9781838987312 https packt link free ebook 9781838987312 a p | ai |
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azure-iot-samples-python | exclamation archived warning all the samples have been moved to our main repository azure iot sdk python https github com azure azure iot sdk python please submit an issue or pr in the azure iot sdk python https github com azure azure iot sdk python repository if there are additional samples you would like to see azure iot samples for python azure iot samples python provides a set of easy to understand continuously tested samples for connecting to azure iot hub via azure azure iot sdk python prerequisites active python release https www python org downloads on your development machine you can verify the current version of python on your development machine using python version or python3 version resources azure iot sdk python https github com azure azure iot sdk python contains the source code for azure iot python sdk azure iot hub documentation https docs microsoft com azure iot hub | server |
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mdt | mdt a police mobile data terminal system designed for use on the fivem platform and esx framework | os |
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vue-boilerplate-template | p align center a href https vuejs org target blank img width 100 src https vuejs org images logo png a p h1 align center strong vue boilerplate template strong h1 div align center a href https twitter com intent tweet text cool url https github com nicejade vue boilerplate template img src https img shields io twitter url https github com nicejade vue boilerplate template blob master assets images logo svg style for the badge alt twitter a div div align center strong vue webpack vuex vue router vue i18n element ui out of the box strong div div align center nice boilerplate template for creating medium plus vue js 2 project div br div align center a href https circleci com gh nicejade vue boilerplate template img src https circleci com gh nicejade vue boilerplate template tree master svg style svg alt build status a a href https nodejs org en img src https img shields io badge node 3e 3d 208 0 0 green svg alt node version a a href https github com nicejade vue boilerplate template img src https img shields io github license nicejade vue boilerplate template svg alt license a a href https hacpai com article 1527681795228 img src https img shields io badge chat hacpai brightgreen svg alt chat a a href https nice lovejade cn zh article vue webpack boilerplate template html img src https img shields io badge chat on 20 20spectrum green svg alt chat a a href https about me nicejade img src https img shields io badge author nicejade 23a696c8 svg alt author nicejade a div br div align center strong a rel noreferrer noopener target blank href https jeffjade com 2018 05 20 140 vue webpack boilerplate template wiki a strong div goal and philosophy for how to build medium sized vue projects provide some reference based on past experience the latest vue boilerplate based on vue cli3 has been open source awesome vue cli3 example https github com nicejade awesome vue cli3 example if you pay attention to it i believe it is very worthwhile prerequisites node js https nodejs org en 4 x 8 x preferred npm version 4 yarn preferred and git https git scm com demo online demo page https blog lovejade cn vue boilerplate template advantage based on vue cli build make more optimization for how to to facilitate the use of vue has already included a lot of commonly used libraries such as vue i18n axios lodash with some experience articles about vue such as vue https jeffjade com 2017 03 11 120 how to write vue better and is still updated make more optimization about how to build the application using webpack webpack http jeffjade com 2017 08 06 124 webpack packge optimization for volume webpack http jeffjade com 2017 08 12 125 webpack package optimization for speed optimize your libraries with webpack https github com googlechromelabs webpack libs optimizations webpack nice tutorial https github com nicejade nice front end tutorial blob master tutorial webpack tutorial md usage git clone https github com nicejade vue boilerplate template your project name cd your project name npm install npm i yarn npm start npm run dev yarn run dev go to http localhost 8080 if port 8080 is already in use on your machine the program will specify the available port incremental for you for example 8081 8082 of course you can temporarily replace the port using the following command port 8888 npm run dev additional supplement you need to make sure that port is a command that can be executed on your machine details summary more command summary npm run build equivalent execution node build js initiate a build project npm run build dll equivalent execution webpack config build webpack dll conf js for more information see webpack dllplugin https webpack js org plugins dll plugin npm run jarvis yarn run jarvis run webpack jarvis https github com zouhir jarvis a very intelligent browser based webpack dashboard in your browser open localhost 1337 you have it jarvis for webpack https raw githubusercontent com nicejade vue boilerplate template master static img jarvis 20for 20webpack png bash npm run pretest using nodejs to build the local server http localhost 3000 do a simple pre test for the code after the package npm run analyz webpack plugin and cli utility that represents bundle content as convenient interactive zoomable treemap it will automatically open this address http localhost 8888 webpack bundle analyzer https cloud githubusercontent com assets 302213 20628702 93f72404 b338 11e6 92d4 9a365550a701 gif details dependent plugin list vue2 vue router vuex vue i18n axios bootstrap element ui lodash moment dayjs js cookie operation request your backend can return the following format data it s better success true message err message content value useful data at the front end you can handle the request like this let params interface required parameters this isloading true this apis modulename getprofile params then result handle the correct data you received catch error this message error error error fin this isloading false so considerate template has been helped to handle the request uniformly so you can be so easy to use of course you can change your own as needed in the helper ajax js file links example https github com nicejade nicelinks vue client nice links https nicelinks site from github about me https about me nicejade first blog https jeffjade com second blog https blog lovejade cn weibo http weibo com jeffjade zhihu https www zhihu com people yang qiong pu segmentfault https segmentfault com u jeffjade jianshu http www jianshu com u 9aae3d8f4c3d twitter https twitter com jeffjade2 facebook https www facebook com yang gang jade writing see the example in the boilerplate template or an example https github com nicejade nicelinks vue client that has been applied online address https nicelinks site license mit http opensource org licenses mit copyright c 2017 present nicejade https about me nicejade | vuejs2 vuex vue-router vue-boilerplate front-end admin pwa lodash vuex3 vue-i18n element-ui | front_end |
masteruah | masteruah information technology bloque 2 nombre github mauroperna https github com mauroperna josetellan https github com josetellan issam49 https github com issam49 eneko lakast https github com enekid joseph reyes https github com jossjack | server |
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openai-cogsrch-fsi | chatgpt enterprise data with azure openai and cognitive search for fsi open in github codespaces https img shields io static v1 style for the badge label github codespaces message open color brightgreen logo github https github com codespaces new hide repo select true ref main repo 599293758 machine standardlinux32gb devcontainer path devcontainer 2fdevcontainer json location westus2 open in remote containers https img shields io static v1 style for the badge label remote 20 20containers message open color blue logo visualstudiocode https vscode dev redirect url vscode ms vscode remote remote containers cloneinvolume url https github com azure samples azure search openai demo this sample was created using content published under https github com azure samples azure search openai demo it has been created to support a scenario in which users are able to ask questions about a bank s financial products this sample demonstrates a few approaches for creating chatgpt like experiences over your own data using the retrieval augmented generation pattern it uses azure openai service to access the chatgpt model gpt 35 turbo and azure cognitive search for data indexing and retrieval rag architecture docs appcomponents png features chat and q a interfaces explores various options to help users evaluate the trustworthiness of responses with citations tracking of source content etc shows possible approaches for data preparation prompt construction and orchestration of interaction between model chatgpt and retriever cognitive search settings directly in the ux to tweak the behavior and experiment with options chat screen docs chatscreen png getting started important in order to deploy and run this example you ll need an azure subscription with access enabled for the azure openai service you can request access here https aka ms oaiapply you can also visit here https azure microsoft com free cognitive search to get some free azure credits to get you started azure resource costs by default this sample will create azure app service and azure cognitive search resources that have a monthly cost as well as form recognizer resource that has cost per document page you can switch them to free versions of each of them if you want to avoid this cost by changing the parameters file under the infra folder though there are some limits to consider for example you can have up to 1 free cognitive search resource per subscription and the free form recognizer resource only analyzes the first 2 pages of each document data please ensure you create a folder called data in the root location and add pdfs for your financial products to it prior to deployment the solution does not have any sample data included prerequisites to run locally azure developer cli https aka ms azure dev install python 3 https www python org downloads important python and the pip package manager must be in the path in windows for the setup scripts to work important ensure you can run python version from console on ubuntu you might need to run sudo apt install python is python3 to link python to python3 node js https nodejs org en download git https git scm com downloads powershell 7 pwsh https github com powershell powershell for windows users only important ensure you can run pwsh exe from a powershell command if this fails you likely need to upgrade powershell note your azure account must have microsoft authorization roleassignments write permissions such as user access administrator https learn microsoft com azure role based access control built in roles user access administrator or owner https learn microsoft com azure role based access control built in roles owner to run in github codespaces or vs code remote containers you can run this repo virtually by using github codespaces or vs code remote containers click on one of the buttons below to open this repo in one of those options open in github codespaces https img shields io static v1 style for the badge label github codespaces message open color brightgreen logo github https github com codespaces new hide repo select true ref main repo 599293758 machine standardlinux32gb devcontainer path devcontainer 2fdevcontainer json location westus2 open in remote containers https img shields io static v1 style for the badge label remote 20 20containers message open color blue logo visualstudiocode https vscode dev redirect url vscode ms vscode remote remote containers cloneinvolume url https github com azure samples azure search openai demo installation project initialization 1 create a new folder and switch to it in the terminal 1 run azd login 1 run azd init t azure search openai demo for the target location the regions that currently support the models used in this sample are east us or south central us for an up to date list of regions and models check here https learn microsoft com en us azure cognitive services openai concepts models starting from scratch execute the following command if you don t have any pre existing azure services and want to start from a fresh deployment 1 run azd up this will provision azure resources and deploy this sample to those resources including building the search index based on the files found in the data folder 1 after the application has been successfully deployed you will see a url printed to the console click that url to interact with the application in your browser it will look like the following output from running azd up assets endpoint png note it may take a minute for the application to be fully deployed if you see a python developer welcome screen then wait a minute and refresh the page use existing resources 1 run azd env set azure openai service name of existing openai service 1 run azd env set azure openai resource group name of existing resource group that openai service is provisioned to 1 run azd env set azure openai chatgpt deployment name of existing chatgpt deployment only needed if your chatgpt deployment is not the default chat 1 run azd env set azure openai gpt deployment name of existing gpt deployment only needed if your chatgpt deployment is not the default davinci 1 run azd up note you can also use existing search and storage accounts see infra main parameters json for list of environment variables to pass to azd env set to configure those existing resources deploying or re deploying a local clone of the repo simply run azd up running locally 1 run azd login 2 change dir to app 3 run start ps1 or start sh or run the vs code task start app to start the project locally sharing environments run the following if you want to give someone else access to completely deployed and existing environment 1 install the azure cli https learn microsoft com cli azure install azure cli 1 run azd init t azure search openai demo 1 run azd env refresh e environment name note that they will need the azd environment name subscription id and location to run this command you can find those values in your azure env name env file this will populate their azd environment s env file with all the settings needed to run the app locally 1 run pwsh scripts roles ps1 this will assign all of the necessary roles to the user so they can run the app locally if they do not have the necessary permission to create roles in the subscription then you may need to run this script for them just be sure to set the azure principal id environment variable in the azd env file or in the active shell to their azure id which they can get with az account show quickstart in azure navigate to the azure webapp deployed by azd the url is printed out when azd completes as endpoint or you can find it in the azure portal running locally navigate to 127 0 0 1 5000 once in the web app try different topics in chat or q a context for chat try follow up questions clarifications ask to simplify or elaborate on answer etc explore citations and sources click on settings to try different options tweak prompts etc resources revolutionize your enterprise data with chatgpt next gen apps w azure openai and cognitive search https aka ms entgptsearchblog azure cognitive search https learn microsoft com azure search search what is azure search azure openai service https learn microsoft com azure cognitive services openai overview faq question why do we need to break up the pdfs into chunks when azure cognitive search supports searching large documents answer chunking allows us to limit the amount of information we send to openai due to token limits by breaking up the content it allows us to easily find potential chunks of text that we can inject into openai the method of chunking we use leverages a sliding window of text such that sentences that end one chunk will start the next this allows us to reduce the chance of losing the context of the text troubleshooting if you see this error while running azd deploy read tmp azd1992237260 backend env lib64 is a directory then delete the app backend backend env folder and re run the azd deploy command this issue is being tracked here https github com azure azure dev issues 1237 | ai |
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bnltk | bnltk build status https travis ci org ashwoolford bnltk svg branch master https travis ci org ashwoolford bnltk license mit https img shields io badge license mit brightgreen svg https opensource org licenses mit bnltk bangla natural language processing toolkit is open source python package for bengali natural language processing it includes modules for tokenization stemming parts of speech tagging i m looking forward to helping form contributors to make this look far better than this installation pip install bnltk usage tokenizer from bnltk tokenize import tokenizers t tokenizers print t bn word tokenizer stemmer from bnltk stemmer import banglastemmer bn stemmer banglastemmer print bn stemmer stem parts of tagger for using the parts of tagger you need to download some data files as follows from bnltk bnltk downloads import datafiles datafiles download after successfully downloading the files then you can use this module from bnltk pos tagger import postagger p tagger postagger p tagger loader sentences print p tagger tagger sentences | nlp-library nlp-machine-learning bangla-nlp deep-learning | ai |
stream-me-up-scotty | div align center img src images scotty gif width 100 height 100 div div align center confluent s solution engineering digital asset repository div this repository contains digital assets created and prepared by confluent s solution engineering team the team will continuously add more content over time take a look below at the current list of assets available their hyperlinks will take you to the right content in the repository series event driven architecture learning series https github com confluentinc stream me up scotty tree main series getting started with cc demos for a list of available demos please click here https github com confluentinc stream me up scotty tree main demos more information on each individual demo can be found on the landing page | confluent-cloud | cloud |
machine-learning-for-software-engineers | top down learning path machine learning for software engineers p align center a href https github com zuzoovn machine learning for software engineers img alt top down learning path machine learning for software engineers src https img shields io badge machine 20learning software 20engineers blue svg a a href https github com zuzoovn machine learning for software engineers stargazers img alt github stars src https img shields io github stars zuzoovn machine learning for software engineers svg a a href https github com zuzoovn machine learning for software engineers network img alt github forks src https img shields io github forks zuzoovn machine learning for software engineers svg a p inspired by coding interview university https github com jwasham coding interview university translations brazilian portuguese https github com zuzoovn machine learning for software engineers blob master readme pt br md https github com zuzoovn machine learning for software engineers blob master readme zh cn md fran ais https github com zuzoovn machine learning for software engineers blob master readme fr fr md https github com zuzoovn machine learning for software engineers blob master readme zh tw md how i nam vu plan to become a machine learning engineer https www codementor io zuzoovn how i plan to become a machine learning engineer a4metbcuk what is it this is my multi month study plan for going from mobile developer self taught no cs degree to machine learning engineer my main goal was to find an approach to studying machine learning that is mainly hands on and abstracts most of the math for the beginner this approach is unconventional because it s the top down and results first approach designed for software engineers please feel free to make any contributions you feel will make it better table of contents what is it what is it why use it why use it how to use it how to use it follow me follow me don t feel you aren t smart enough dont feel you arent smart enough about video resources about video resources prerequisite knowledge prerequisite knowledge the daily plan the daily plan motivation motivation machine learning overview machine learning overview machine learning mastery machine learning mastery machine learning is fun machine learning is fun inky machine learning inky machine learning machine learning an in depth guide machine learning an in depth guide stories and experiences stories and experiences machine learning algorithms machine learning algorithms beginner books beginner books practical books practical books kaggle knowledge competitions kaggle knowledge competitions video series video series mooc mooc resources resources becoming an open source contributor becoming an open source contributor games games podcasts podcasts communities communities conferences conferences interview questions interview questions my admired companies my admired companies why use it i m following this plan to prepare for my near future job machine learning engineer i ve been building native mobile applications android ios blackberry since 2011 i have a software engineering degree not a computer science degree i have an itty bitty amount of basic knowledge about calculus linear algebra discrete mathematics probability statistics from university think about my interest in machine learning can i learn and get a job in machine learning without studying cs master and phd https www quora com can i learn and get a job in machine learning without studying cs master and phd you can but it is far more difficult than when i got into the field drac smith https www quora com can i learn and get a job in machine learning without studying cs master and phd answer drac smith srid ot0p how do i get a job in machine learning as a software programmer who self studies machine learning but never has a chance to use it at work https www quora com how do i get a job in machine learning as a software programmer who self studies machine learning but never has a chance to use it at work i m hiring machine learning experts for my team and your mooc will not get you the job there is better news below in fact many people with a master s in machine learning will not get the job because they and most who have taken moocs do not have a deep understanding that will help me solve my problems ross c taylor https www quora com how do i get a job in machine learning as a software programmer who self studies machine learning but never has a chance to use it at work answer ross c taylor srid ot0p what skills are needed for machine learning jobs http programmers stackexchange com questions 79476 what skills are needed for machine learning jobs first you need to have a decent cs math background ml is an advanced topic so most textbooks assume that you have that background second machine learning is a very general topic with many sub specialties requiring unique skills you may want to browse the curriculum of an ms program in machine learning to see the course curriculum and textbook uri http softwareengineering stackexchange com a 79717 probability distributed computing and statistics hydrangea http softwareengineering stackexchange com a 79575 i find myself in times of trouble afaik there are two sides to machine learning http machinelearningmastery com programmers can get into machine learning practical machine learning this is about querying databases cleaning data writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions it s the mess of reality theoretical machine learning this is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible it is a whole lot neater and cleaner and removed from the mess of reality i think the best way for practice focused methodology is something like practice learning practice http machinelearningmastery com machine learning for programmers comment 358985 that means where students first come with some existing projects with problems and solutions practice to get familiar with traditional methods in the area and perhaps also with their methodology after practicing with some elementary experiences they can go into the books and study the underlying theory which serves to guide their future advanced practice and will enhance their toolbox of solving practical problems studying theory also further improves their understanding on the elementary experiences and will help them acquire advanced experiences more quickly it s a long plan it s going to take me years if you are familiar with a lot of this already it will take you a lot less time how to use it everything below is an outline and you should tackle the items in order from top to bottom i m using github s special markdown flavor including tasks lists to check progress x create a new branch so you can check items like this just put an x in the brackets x more about github flavored markdown https guides github com features mastering markdown github flavored markdown follow me i m a vietnamese software engineer who is really passionate and wants to work in the usa how much did i work during this plan roughly 4 hours night after a long hard day at work i m on the journey twitter nam vu https twitter com zuzoovn nam vu top down learning path machine learning for software engineers http sv1 upsieutoc com 2016 10 08 331f241c8da44d0c43e9324d55440db6 md jpg usa as heck don t feel you aren t smart enough i get discouraged from books and courses that tell me as soon as i open them that multivariate calculus inferential statistics and linear algebra are prerequisites i still don t know how to get started what if i m not good at mathematics http machinelearningmastery com what if im not good at mathematics 5 techniques to understand machine learning algorithms without the background in mathematics http machinelearningmastery com techniques to understand machine learning algorithms without the background in mathematics how do i learn machine learning https www quora com machine learning how do i learn machine learning 1 about video resources some videos are available only by enrolling in a coursera or edx class it is free to do so but sometimes the classes are no longer in session so you have to wait a couple of months so you have no access i m going to be adding more videos from public sources and replacing the online course videos over time i like using university lectures prerequisite knowledge this short section consists of prerequisites interesting info i wanted to learn before getting started on the daily plan what is the difference between data analytics data analysis data mining data science machine learning and big data https www quora com what is the difference between data analytics data analysis data mining data science machine learning and big data 1 learning how to learn https www coursera org learn learning how to learn don t break the chain http lifehacker com 281626 jerry seinfelds productivity secret how to learn on your own https metacademy org roadmaps rgrosse learn on your own the daily plan each subject does not require a whole day to be able to understand it fully and you can do multiple of these in a day each day i take one subject from the list below read it cover to cover take notes do the exercises and write an implementation in python or r motivation dream https www youtube com watch v g jwwyx7jlo machine learning overview a visual introduction to machine learning http www r2d3 us visual intro to machine learning part 1 gentle guide to machine learning https blog monkeylearn com gentle guide to machine learning introduction to machine learning for developers http blog algorithmia com introduction machine learning developers machine learning basics for a newbie https www analyticsvidhya com blog 2015 06 machine learning basics how do you explain machine learning and data mining to non computer science people https www quora com how do you explain machine learning and data mining to non computer science people machine learning under the hood blog post explains the principles of machine learning in layman terms simple and clear https georgemdallas wordpress com 2013 06 11 big data data mining and machine learning under the hood what is machine learning and how does it work https www youtube com watch v elojmnjn4kk list pl5 da3qgb5icembquqbbcoqwcs6oybr5a index 1 deep learning a non technical introduction http www slideshare net alfredpong1 deep learning a nontechnical introduction 69385936 removed machine learning mastery the machine learning mastery method http machinelearningmastery com machine learning mastery method machine learning for programmers http machinelearningmastery com machine learning for programmers applied machine learning with machine learning mastery http machinelearningmastery com start here python machine learning mini course http machinelearningmastery com python machine learning mini course machine learning algorithms mini course http machinelearningmastery com machine learning algorithms mini course machine learning is fun machine learning is fun https medium com ageitgey machine learning is fun 80ea3ec3c471 37ue6caww part 2 using machine learning to generate super mario maker levels https medium com ageitgey machine learning is fun part 2 a26a10b68df3 kh7qgvp1b part 3 deep learning and convolutional neural networks https medium com ageitgey machine learning is fun part 3 deep learning and convolutional neural networks f40359318721 44rhxy637 part 4 modern face recognition with deep learning https medium com ageitgey machine learning is fun part 4 modern face recognition with deep learning c3cffc121d78 3rwmq0ddc part 5 language translation with deep learning and the magic of sequences https medium com ageitgey machine learning is fun part 5 language translation with deep learning and the magic of sequences 2ace0acca0aa wyfthap4c part 6 how to do speech recognition with deep learning https medium com ageitgey machine learning is fun part 6 how to do speech recognition with deep learning 28293c162f7a lhr1nnpcy part 7 abusing generative adversarial networks to make 8 bit pixel art https medium com ageitgey abusing generative adversarial networks to make 8 bit pixel art e45d9b96cee7 part 8 how to intentionally trick neural networks https medium com ageitgey machine learning is fun part 8 how to intentionally trick neural networks b55da32b7196 inky machine learning https triskell github io 2016 11 15 inky machine learning html part 1 what is machine learning https triskell github io 2016 10 23 what is machine learning html part 2 supervised learning and unsupervised learning https triskell github io 2016 11 13 supervised learning and unsupervised learning html machine learning an in depth guide overview goals learning types and algorithms http www 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path your mentor to become a machine learning expert https www analyticsvidhya com learning path learn machine learning you too can become a machine learning rock star no phd https backchannel com you too can become a machine learning rock star no phd necessary 107a1624d96b g9p16ldp7 how to become a data scientist in 6 months a hacker s approach to career planning video https www youtube com watch v riofv14c0tc slide http www slideshare net tetianaivanova2 how to become a data scientist in 6 months 5 skills you need to become a machine learning engineer http blog udacity com 2016 04 5 skills you need to become a machine learning engineer html are you a self taught machine learning engineer if yes how did you do it how long did it take you https www quora com are you a self taught machine learning engineer if yes how did you do it how long did it take you how can one become a good machine learning engineer https www quora com how can one become a good machine learning engineer a learning sabbatical focused on machine learning http karlrosaen com ml machine learning algorithms 10 machine learning algorithms explained to an army soldier https www analyticsvidhya com blog 2015 12 10 machine learning algorithms explained army soldier top 10 data mining algorithms in plain english https rayli net blog data top 10 data mining algorithms in plain english 10 machine learning terms explained in simple english http blog aylien com 10 machine learning terms explained in simple a tour of machine learning algorithms http machinelearningmastery com a tour of machine learning algorithms the 10 algorithms machine learning engineers need to know https gab41 lab41 org the 10 algorithms machine learning engineers need to know f4bb63f5b2fa ofc7t2965 comparing supervised learning algorithms http www dataschool io comparing supervised learning algorithms machine learning algorithms a collection of minimal and clean implementations of machine learning algorithms https github com rushter mlalgorithms knn algorithm in machine learning https www scaler com topics what is knn algorithm in machine learning beginner books data smart using data science to transform information into insight 1st edition https www amazon com data smart science transform information dp 111866146x data science for business what you need to know about data mining and data analytic thinking https www amazon com data science business data analytic thinking dp 1449361323 predictive analytics the power to predict who will click buy lie or die https www amazon com predictive analytics power predict click dp 1118356853 practical books machine learning for hackers https www amazon com machine learning hackers drew conway dp 1449303714 github repository r https github com johnmyleswhite ml for hackers github repository python https github com carljv will it python python machine learning https www amazon com python machine learning sebastian raschka ebook dp b00ysilnl0 github repository https github com rasbt python machine learning book programming collective intelligence building smart web 2 0 applications https www amazon com programming collective intelligence building applications ebook dp b00f8qdzwg machine learning an algorithmic perspective second edition https www amazon com machine learning algorithmic perspective recognition dp 1466583282 github repository https github com alexsosn marslandmlalgo resource repository http seat massey ac nz personal s r marsland mlbook html introduction to machine learning with python a guide for data scientists http shop oreilly com product 0636920030515 do github repository https github com amueller introduction to ml with python data mining practical machine learning tools and techniques third edition https www amazon com data mining practical techniques management dp 0123748569 teaching material slides for chapters 1 5 zip http www cs waikato ac nz ml weka slides3rded ch1 5 zip slides for chapters 6 8 zip http www cs waikato ac 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universities stanford http ai stanford edu courses machine learning summer schools http mlss cc oxford https www cs ox ac uk people nando defreitas machinelearning cambridge http mlg eng cam ac uk flipboard topics machine learning https flipboard com topic machinelearning deep learning https flipboard com topic deeplearning artificial intelligence https flipboard com topic artificialintelligence medium topics machine learning https medium com tag machine learning latest deep learning https medium com tag deep learning artificial intelligence https medium com tag artificial intelligence monthly top 10 articles machine learning https medium mybridge co search q 22machine 20learning 22 algorithms https medium mybridge co search q algorithms comprehensive list of data science resources http www datasciencecentral com group resources forum topics comprehensive list of data science resources digitalmind s artificial intelligence resources http blog digitalmind io post artificial intelligence resources awesome machine learning https github com josephmisiti awesome machine learning awesome graph classification https github com benedekrozemberczki awesome graph classification awesome community detection https github com benedekrozemberczki awesome community detection creativeai s machine learning http www creativeai net cat 5b0 5d machine learning machine learning online courses https classpert com machine learning games halite a i coding game https halite io vindinium a i programming challenge http vindinium org general video game ai competition http www gvgai net angry birds ai competition https aibirds org the ai games http theaigames com fighting game ai competition http www ice ci ritsumei ac jp ftgaic codecup http www codecup nl intro php student starcraft ai tournament http sscaitournament com aiide starcraft ai competition http www cs mun ca dchurchill starcraftaicomp cig starcraft ai competition https sites google com site starcraftaic codingame ai bot games https www codingame com training machine learning becoming an open source contributor tensorflow magenta magenta music and art generation with machine intelligence https github com tensorflow magenta tensorflow tensorflow computation using data flow graphs for scalable machine learning https github com tensorflow tensorflow cmusatyalab openface face recognition with deep neural networks https github com cmusatyalab openface tensorflow models syntaxnet neural models of syntax https github com tensorflow models tree master syntaxnet podcasts podcasts for beginners talking machines http www thetalkingmachines com linear digressions http lineardigressions com data skeptic http dataskeptic com this week in machine learning ai https twimlai com machine learning guide http ocdevel com podcasts machine learning interviews with ml practitioners researchers and kagglers about their joureny chai time data science https www youtube com playlist list pllvvxm0q8zubindoiazgzlenmxvz9bd3x audio http anchor fm chaitimedatascience writeups https sanyambhutani com tag chaitimedatascience machine learning for beginners interviews https www youtube com channel ucdz0gx f3ulmkfxtyzsfbaw audio https jayshah buzzsprout com more advanced podcasts partially derivative http partiallyderivative com o reilly data show http radar oreilly com tag oreilly data show podcast not so standard deviation https soundcloud com nssd podcast podcasts to think outside the box data stories http datastori es communities quora machine learning https www quora com topic machine learning statistics https www quora com topic statistics academic discipline data mining https www quora com topic data mining reddit machine learning https www reddit com r machinelearning computer vision https www reddit com r computervision natural language https www reddit com r languagetechnology data science https www reddit com r datascience big data https www reddit com r bigdata statistics https www reddit com r statistics data tau http www datatau com deep learning news http news startup ml kdnuggets http www kdnuggets com conferences neural information processing systems nips https nips cc international conference on learning representations iclr http www iclr cc doku php id iclr2017 main redirect 1 association for the advancement of artificial intelligence aaai http www aaai org conferences aaai aaai17 php ieee conference on computational intelligence and games cig http www ieee cig org ieee international conference on machine learning and applications icmla http www icmla conference org international conference on machine learning icml https 2017 icml cc international joint conferences on artificial intelligence ijcai http www ijcai org association for computational linguistics acl http acl2017 org interview questions how to prepare for a machine learning interview http blog udacity com 2016 05 prepare machine learning interview html 40 interview questions asked at startups in machine learning data science https www analyticsvidhya com blog 2016 09 40 interview questions asked at startups in machine learning data science 21 must know data science interview questions and answers http www kdnuggets com 2016 02 21 data science interview questions answers html top 50 machine learning interview questions answers http career guru99 com top 50 interview questions on machine learning machine learning engineer interview questions https resources workable com machine learning engineer interview questions popular machine learning interview questions http www learn4master com machine learning popular machine learning interview questions what are some common machine learning interview questions https www quora com what are some common machine learning interview questions what are the best interview questions to evaluate a machine learning researcher https www quora com what are the best interview questions to evaluate a machine learning researcher collection of machine learning interview questions http analyticscosm com machine learning interview questions for data scientist interview 121 essential machine learning questions answers https elitedatascience com mlqa reading list minimum viable study plan for machine learning interviews https github com khangich machine learning interview my admired companies elsa your virtual pronunciation coach https www elsanow io home | machine-learning deep-learning artificial-intelligence software-engineer machine-learning-algorithms | ai |
sysdesign | sysdesign code base for computer system design | os |
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Intel-8085 | intel 8085 processor a repository for the intel 8085 processor intended for embedded system design and electronics applications img src images kl intel p8085ah jpg width 70 height 70 br img src images 8085 png width 85 height 85 br reference links hardware simple testing circuit for 8085 freerun http saundby com electronics 8085 freerun shtml andreas spiess 8085 platform https easyeda com editor id 85b1b86d482748c79392f254dd90f14a 6faec151f2224e999d9fba18e1097c8b professor diwakar yagyasen microprocessor lecture notes http dylucknow weebly com microprocessor html software sb assembler 3 cross assembler for the 8085 https www sbprojects net sbasm index php python needed for sb assembler 3 https www python org intel 8085 microprocessor related wikipedia intel 8085 https en wikipedia org wiki intel 8085 diwakar yagyasen interrupts on 8085 http dylucknow weebly com uploads 6 7 3 1 6731187 8085 interrupts pdf al najaf technical college interupts https cnj atu edu iq wp content uploads 2019 09 lect11 interrupt pdf dhananjay v gadre nist 8085 projects the compendium http 8085projects in assembly programming andreas spiess 8085 assembler program examples https github com sensorsiot 8085 computer intel 8080 8085 assembly language programming manual http bitsavers trailing edge com components intel mcs80 9800301d 8080 8085 assembly language programming manual may81 pdf assembly language programming of 8085 pdf https myethiolectures files wordpress com 2015 06 programming 8085 pdf instruction set of 8085 https www javatpoint com instruction set of 8085 apuntes del microprocesador 8085 lenguaje assembler https www scribd com document 193365760 apuntes del microprocesador 8085 lenguaje assembler videos simple testing circuit for 8085 https www youtube com watch v otq ktkzshy simple 8085 platform with 8155 part1 andreas spiess https www youtube com watch v 45elcavb5xq simple 8085 platform with 8155 part1 andreas spiess https www youtube com watch v qizt0epfeza lcd 16x2 hd44780 lcd initialization http web alfredstate edu faculty weimandn lcd lcd initialization lcd initialization index html | os |
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fun-phonegap-plugins | fun phonegap plugins i enjoy using phonegap http phonegap com for mobile development but also need to utilize some native features on android and ios this project includes some of my base plugins that i ll utilize for other projects please see the readme md in each plugin directory for instructions on how to add it to your project each plugin directory includes a sample phonegap project which should be runnable on your emulator or device i am running phonegap 2 6 0 http docs phonegap com en 2 6 0 index html and jquery mobile 1 3 1 http jquerymobile com i hope to try sencha touch in the future as well project structure this project will be organized as follows fun phonegap plugins android plugin name android readme md info about plugin name here other plugin android ios coming soon plugin name ios yet another plugin ios license the mit license permission is hereby granted free of charge to any person obtaining a copy of this software and associated documentation files the software to deal in the software without restriction including without limitation the rights to use copy modify merge publish distribute sublicense and or sell copies of the software and to permit persons to whom the software is furnished to do so subject to the following conditions the above copyright notice and this permission notice shall be included in all copies or substantial portions of the software the software is provided as is without warranty of any kind express or implied including but not limited to the warranties of merchantability fitness for a particular purpose and noninfringement in no event shall the authors or copyright holders be liable for any claim damages or other liability whether in an action of contract tort or otherwise arising from out of or in connection with the software or the use or other dealings in the software | front_end |
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MIS6300 | mis6300 the repository is for mis6300 information technology class you can find sql r and python code here | server |
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crawler | p align center a href https www crwlr software target blank img src https github com crwlrsoft graphics blob eee6cf48ee491b538d11b9acd7ee71fbcdbe3a09 crwlr logo png alt crwlr software logo width 260 a p library for rapid web crawler and scraper development this library provides kind of a framework and a lot of ready to use so called steps that you can use as building blocks to build your own crawlers and scrapers with to give you an overview here s a list of things that it helps you with crawler politeness https www crwlr software packages crawler the crawler politeness 128519 respecting robots txt throttling load urls using a psr 18 http client https www crwlr software packages crawler the crawler loaders default is of course guzzle or a headless browser https www crwlr software packages crawler the crawler loaders using a headless browser chrome to get source after javascript execution get absolute links from html documents https www crwlr software packages crawler included steps html html get link x1f517 get sitemaps from robots txt and get all urls from those sitemaps https www crwlr software packages crawler included steps sitemap crawl load all pages of a website https www crwlr software packages crawler included steps http crawling x1f577 use cookies or don t https www crwlr software packages crawler the crawler loaders http loader x1f36a use any http methods get post and send any headers or body https www crwlr software packages crawler included steps http http requests easily iterate over paginated list pages https www crwlr software packages crawler included steps http paginating x1f501 extract data from html https www crwlr software packages crawler included steps html extracting data and also xml https www crwlr software packages crawler included steps xml using css selectors or xpath queries json https www crwlr software packages crawler included steps json using dot notation csv https www crwlr software packages crawler included steps csv map columns extract schema org structured data https www crwlr software packages crawler included steps html schema org in json ld format from html documents keep memory usage low https www crwlr software packages crawler crawling procedure memory usage by using php generators x1f4aa cache http responses https www crwlr software packages crawler response cache during development so you don t have to load pages again and again after every code change get logs https www crwlr software packages crawler the crawler loggers about what your crawler is doing accepts any psr 3 loggerinterface and a lot more documentation you can find the documentation at crwlr software https www crwlr software packages crawler getting started contributing if you consider contributing something to this package read the contribution guide contributing md contributing md | crawling php scraper scraping scraping-websites web-crawler web-crawling web-scraping hacktoberfest crawler web-scraper | front_end |
dtu_mlops | p align center h1 align center machine learning operations h1 p align center repository for a href https kurser dtu dk course 02476 course 02476 a at dtu p p align center strong a href https skaftenicki github io dtu mlops checkout the homepage a strong p p p align center img src figures mlops cycle png width 1000 p course information course responsible postdoc nicki skafte detlefsen https skaftenicki github io nsde dtu dk professor s ren hauberg http www2 compute dtu dk sohau sohau dtu dk 5 ects european credit transfer system corresponding to 140 hours of work 3 week period of january 2023 master course grade pass not passed type of assessment weekly project updates final oral examination presentation recommended prerequisites dtu course 02456 deep learning https kurser dtu dk course 2021 2022 02456 or experience with the following topics general understanding of machine learning datasets probability classifiers overfitting etc basic knowledge about deep learning backpropagation convolutional neural networks auto encoders etc coding in pytorch https pytorch org the first day we provide a number of exercises in pytorch to get everyone s skills up to date as fast as possible course setup start by cloning or downloading this repository bash git clone https github com skaftenicki dtu mlops if you do not have git installed yet we will touch upon it in the course the folder will contain all exercise material for this course and lectures additionally you should join our slack channel https join slack com t dtumlops shared invite zt 1j1zx8t4h ntbupibr9xcz58erdyyikw which we use for communication link may be expired write to me mailto skaftenicki gmail com course organization we highly recommend that when going through the material that you use the homepage https skaftenicki github io dtu mlops which is the corresponding github pages https pages github com version of this repository that is more nicely rendered that also includes some special html magic provided by just the docs https github com just the docs just the docs the course is divided into sessions denoted by capital s and modules denoted by capital m a session corresponds to full day of work if you are following the course meaning approx 9 hours of work each session s corresponds to topic within mlops and consist of multiple modules m that each covers an tool within the session importantly we differ between core modules and optional modules core modules will be marked by info core module at the top of their corresponding page core modules are important to go through to be able to pass the course you are highly recommended to still do the optional modules mlops what is it machine learning operations mlops is a rather new field that has seen its uprise as machine learning and particular deep learning has become a technology that is widely available the term itself is a compound of machine learning and operations and covers everything that has to do with the management of the production ml lifecycle the lifecycle of production ml can largely be divided into three phases 1 design the initial phase starts with a investigation of the problem based on this analysis a number of requirements can be prioritized of what we want our future model to actually do since machine learning requires data to be trained we also investigate in this step what data we have and if we need to source it in some other way 2 model development based on the design phase we can actually begin to conjurer some machine learning algorithm to solve our problems as always the initial step often involve doing some data analysis to make sure that our model is actually learning the signal that we want it to learn secondly is the machine learning engineering phase where the particular model architecture is chosen finally we also need to do validation and testing to make sure that our model is generalizing well 3 operations based on the model development phase we now have a model and we actual want to use the operations is where create an automatic pipeline that makes sure that whenever we make changes to our codebase they gets automatically incorporated into our model such that we do not slow down production equally important is also the ongoing monitoring of already deployed models to make sure that they behave exactly as we specified them it is important to note that the three steps are in fact a cycle meaning that we you have successfully deployed a machine learning model that is not the end of it your initial requirements may change forcing you to revisit the design phase some new algorithm may show promising results so you revisit the model development phase to implement this and finally you may try to cut the cost of running your model in production making you revisit the operations phase trying to optimize some steps the focus in this course is particular on the operations part of mlops as this is what many data scientist are missing in their toolbox to take all the knowledge they have about data processing and model development into a production setting learning objectives general course objective introduce the student to a number of coding practices that will help them organization scale monitor and deploy machine learning models either in a research or production setting to provide hands on experience with a number of frameworks both local and in the cloud for doing large scale machine learning models this includes organize code in a efficient way for easy maintainability and shareability understand the importance of reproducibility and how to create reproducible containerized applications and experiments cable of using version control to efficiently collaborate on code development knowledge of continuous integration ci and continuous machine learning cml for automating code development being able to debug profile visualize and monitor multiple experiments to assess model performance cable of using online cloud based computing services to scale experiments demonstrate knowledge about different distributed training paradigms within machine learning and how to apply them deploy machine learning models both locally and in the cloud conduct a research project in collaboration with follow students using the frameworks taught in the course have lots of fun and share memes references additional reading resources in no particular order ref 1 https towardsdatascience com ml ops machine learning as an engineering discipline b86ca4874a3f introduction blog post for those that have never heard about mlops and want to get an overview ref 2 https cloud google com architecture mlops continuous delivery and automation pipelines in machine learning great document from google about the different levels of mlops ref 3 https ml ops org content mlops principles another introduction to the principles of mlops and the different stages of mlops ref 4 https papers nips cc paper 2015 file 86df7dcfd896fcaf2674f757a2463eba paper pdf great paper about the technical depth in machine learning ref 5 https arxiv org abs 2209 09125 interview study that uncovers many of the pain points that ml engineers go through when doing mlops other courses with content similar to this made with ml https madewithml com great online mlops course that also covers additional topics on the foundations of working with ml full stack deep learning https fullstackdeeplearning com another mlops online course the does through the hole developer pipeline mlops zoomcamp https github com datatalksclub mlops zoomcamp mlops online course that includes many of the same topics contributing if you want to contribute to the course we are happy to have you anything from fixing typos to adding new content is welcome for building the course material locally it is a simple two step process bash pip install r requirements txt mkdocs serve which will start a local server that you can access at localhost 8000 and will automatically update when you make changes to the course material when you have something that you want to contribute please make a pull request license i highly value open source and the content of this course is therefore free to use under the apache 2 0 license if you use parts of this course in your own work please cite using bibtex misc skafte mlops author nicki skafte detlefsen title machine learning operations howpublished url https github com skaftenicki dtu mlops year 2022 | ai |
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INFORMATION-TECHNOLOGY-COMMUNITY | h1 align center ukm itc nbsp nbsp h1 h4 align center unit kegiatan mahasiswa information technology community h3 div align center img src static img img itc png br div view project div align center strong login form strong br img src static img img frame 2019 png height 500px vspace 20 strong daashboard strong br img src static img img frame 2020 png height 500px vspace 20 strong visualisasi data strong br img src static img img frame 2021 png height 500px vspace 20 strong anggota strong br img src static img img frame 2022 png height 500px vspace 20 strong bidang atau devisi strong br img src static img img frame 2023 png height 500px vspace 20 strong program kerja strong br img src static img img frame 2024 png height 500px vspace 20 strong laporan strong br img src static img img frame 2025 png height 500px vspace 20 strong notifikasi strong br img src static img img frame 2026 png height 500px vspace 20 div setup project strong instalasi strong nbsp nbsp install python python official https www python org nbsp nbsp clone repository bash git clone https github com enonglosker information technology community git nbsp nbsp buat env bash python m venv env nbsp nbsp aktifkan env bash env scripts activate nbsp nbsp masuk ke folder bash cd information technology community nbsp nbsp install requirements bash pip install r requirement txt nbsp nbsp run server bash python manage py runserver br contributors thanks to all the people who contribute a href https github com enonglosker information technology community graphs contributors img src https opencollective com information technology community contributors svg width 890 a | server |
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bowl | p align center image src https github com classicemi bowl js blob develop assets logo png raw true width 128 p bowl js npm https img shields io npm v bowl js svg style flat square https www npmjs com package bowl js npm https img shields io npm dt bowl js svg style flat square https www npmjs com package bowl js license https img shields io github license elemefe bowl svg style flat square https github com elemefe bowl github stars https img shields io github stars elemefe bowl svg style social label star https github com elemefe bowl static resources front end storage solving strategy links documentation https elemefe github io bowl screenshot https raw githubusercontent com classicemi bowl develop assets demo gif quick start for those resources that need to be cached you do not have to insert script tags to the pages just write a little piece of javascript and bowl will take care of it html script var bowl new bowl bowl add url dist vendor hash js key vendor url dist app hash js key app url dist style hash css key style bowl inject then do some stuff script bowl will add these resources to cache currently localstorage whenever the url of the resources get modified bowl will update the files in the cache for more useful functions of bowl just checkout the api document https elemefe github io bowl development setup after cloning the repo run shell yarn install yep yarn is recommended commonly used npm scripts shell watch and auto rebuild lib bowl js and lib bowl min js npm run dev watch and auto re run unit tests in chrome npm run test unit build all dist files npm run build license mit | front_end |
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paradise | paradise collection of amazing effects paradise dtysky moe paradise dtysky moe contribute if you want to join this project and create your effect 1 clone this project and create a branch 2 run npm run create then you will see your effect folder is under src collection 3 edit src routes config add your effect to routes 4 run npm run dev open localhost 8888 to develop 5 push your branch and create a merge request to master current effects rainbowstarwave http paradise dtysky moe effect rainbow star wave rainbowstarwave src collection rainbowstarwave cover jpg treesgenerator2d http paradise dtysky moe effect trees generator 2d treesgenerator2d src collection treesgenerator2d cover jpg digitalclock3d http paradise dtysky moe effect digital clock 3d digitalclock3d src collection digitalclock3d cover jpg lottiehelloworld http paradise dtysky moe effect lottie hello world lottiehelloworld src collection lottiehelloworld cover jpg pixeldisplacement2d http paradise dtysky moe effect pixel displacement 2d pixeldisplacement2d src collection pixeldisplacement2d cover jpg particle3dbythree http paradise dtysky moe effect particle 3d by three particle3dbythree src collection particle3dbythree cover jpg panoramaimageviewer http paradise dtysky moe effect panorama image viewer panoramaimageviewer src collection panoramaimageviewer cover jpg shaderwaterripple http paradise dtysky moe effect shader water ripple shaderwaterripple src collection shaderwaterripple cover jpg imagefragmenttransition http paradise dtysky moe effect image fragment transition imagefragmenttransition src collection imagefragmenttransition cover jpg | front_end |
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web-v2 | a react template built with vite https cn vitejs dev chakra ui https chakra ui com react router https reactrouter com web react icons https react icons github io react icons | react | front_end |
blockchain2graph | build status https travis ci org straumat blockchain2graph svg branch development https travis ci org straumat blockchain2graph codacy badge https api codacy com project badge grade 99d74d003bbc4f56abed38301003c0b0 https www codacy com app stephane traumat blockchain2graph utm source github com amp utm medium referral amp utm content straumat blockchain2graph amp utm campaign badge grade blockchain2graph extracts blockchain data bitcoin and insert them into a graph database neo4j blockchain2graph console https raw githubusercontent com straumat blockchain2graph development docs images b2g console screenshot png here are some use cases query blockchain data with the cypher query language https neo4j com developer cypher query language build web sites like blockchain info https blockchain info add meta information to addresses and transactions we would love to add your use case here contacts us at blockchain inspector http www blockchaininspector com we are using artificial intelligence to fight fraud in the blockchain and we needed to have a convenient way to access blockchain information with blockchain2graph we can analyse blockchain data as transactions between nodes and add meta information on them the documentation can be found here https github com straumat blockchain2graph wiki developped by st phane traumat https about me straumat from scub https www scub net blockchain2graph is released under version 3 0 of the gnu general public licence https github com straumat blockchain2graph blob master license | bitcoin neo4j java graph blockchain data-science datascience data | blockchain |
nlp_mipt | nlp mipt https vk com nlp mipt | ai |
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nlp_workshop_dhs18 | getting started with natural language processing workshop datahack summit 2018 assets main banner png this repository contains code and presentation for our full day workshop getting started with natural language processing this is created for the purpose of being presented in analytics vidhya s datahack summit 2018 authors dipanjan sarkar https www linkedin com in dipanzan amp raghav bali https www linkedin com in baliraghav structure of the workshop introduction to natural language processing text pre processing and wrangling removing html tags noise removing accented characters removing special characters symbols handling contractions stemming lemmatization stop word removal project build a duplicate character removal module project build a spell check and correction module project build an end to end text pre processor text understanding pos parts of speech tagging text parsing shallow parsing dependency parsing constituency parsing ner named entity recognition tagging project build your own pos tagger project build your own ner tagger text representation feature engineering traditional statistical models bow tf idf newer deep learning models for word embeddings word2vec glove fasttext project movie recommendations project sentiment analysis using unsupervised learning project sentiment analysis using supervised learning project text clustering grouping similar movies project topic models project text summarization promise of deep learning for nlp key takeaways learn and understand popular nlp workflows with interactive examples covers concepts and interactive projects on cleaning and handling noisy unstructured text data including duplicate checks spelling corrections and text wrangling build your own pos and ner taggers and parse text data to understand it better understand build and explore text semantics and representations with traditional statistical models and newer word embedding models projects on popular nlp tasks including text classification sentiment analysis text clustering summarization topic models and recommendations brief coverage of the promise of deep learning for nlp system requirements standard system with 4 8gb ram 2 4 core processor i5 i7 amd gpu preferred for some deep learning tasks but not essential windows linux mac os cloud based services like aws ec2 also work fine notes participants needs to carry their laptop for the workshop anaconda distribution python 3 6 preferred with the following libraries pre installed nltk spacy textblob scikit learn numpy pandas keras tensorflow if you install python 3 7 do remember that keras tensorflow may not be available with a stable build | ai |
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erdapfel | erdapfel h1 align center img src https github com qwant qwantmaps raw master images logo png alt qwantmaps height 200 h1 erdapfel is qwant maps https www qwant com maps front end application it is a javascript single page app that allows to browse the map search for places see your position on the map etc qwant maps screenshot https user images githubusercontent com 442681 192721720 1cca02f8 dec2 45b9 af1a 54c5078acec7 png the project s documentation is available on the repo s wiki https github com qwant erdapfel wiki for a global overview of qwant maps and more details about each component check out qwantmaps https github com qwant qwantmaps repo license github license https img shields io github license qwant erdapfel svg https github com qwant erdapfel blob master license this project is licensed under the apache license 2 0 please note that it depends on many other opensource projects that have their own terms and conditions | qwant-maps mapbox-gl-js maps qwant frontend map | front_end |
design-system | this repository is deprecated use https github com wikia fandom frontend instead fandom design system reference page and documentation are available at http fandomdesignsystem com http fandomdesignsystem com setup to install packages you need to set artifactory npm token environment value first you might already have this token set in your global npmrc file because you ve executed npm login scope fandom script before in order to make your life easier we prepared a command that will retrieve this token automatically just run this command shell source scripts set artifactory token sh deploying test version to deploy test version you need to run shell yarn release test this command will update package patch version it will append test number tag if you need to use another tag i e if tag is already in use you can pass it as argument to release test script like so shell yarn release test custom tag e g yarn release test my test running release test command multiple times will increment tag number so you can deploy multiple versions confluence page https wikia inc atlassian net wiki display desys design system contributors contribute to this project http fandomdesignsystem com overview contributing see all contributors on github https github com wikia design system graphs contributors i18n localization messages for design system components crowdin see https wikia inc atlassian net wiki display int i18n tools for information on getting the design system i18n files to and from crowdin copyright code and documentation copyright 2018 fandom inc note code and images contained within this repo are not licensed for general use please contact us at http fandom wikia com about contact if you re interested in licensing any part of this repo installation git clone repository url this repository cd my app yarn install running development yarn dev visit your app at http localhost 4200 http localhost 4200 visit your tests at http localhost 4200 tests http localhost 4200 tests code generators make use of the many generators for code try ember help generate for more details running tests ember test ember test server linting yarn lint hbs yarn lint js yarn lint js fix further reading useful links ember js https emberjs com ember cli https ember cli com development browser extensions ember inspector for chrome https chrome google com webstore detail ember inspector bmdblncegkenkacieihfhpjfppoconhi ember inspector for firefox https addons mozilla org en us firefox addon ember inspector | design design-system | os |
PoisePMS | poisepms this application allows employees at a fictitious structural engineering company called poised to capture information about building projects projects can be searched for edited and marked as complete all overdue projects can be viewed as well as current projects description information about all projects or specific projects can be viewed specific projects can be searched for using either the project name or number and then edited projects can be marked as finalised and the date of completion is requested by the user if the customer still has an outstanding amount to be paid an invoice is generated that includes the customer s details in addition a list of overdue projects can be viewed the following information about each project is stored in a mysql database project number unique id project name building type house shopping mall office block apartment etc physical address erf number zoning number total project cost to the customer amount paid to date project deadline the name phone number email address and work address of the following people architect contractor customer project manager structural engineer dependencies java database connectivity mysql api is used to communicate with the db server import the following libraries java sql java time localdate java util images main menu options main menus screenshot https github com nadia jsch poisepms blob master main 20menu png sub menu options sub menu screenshot https github com nadia jsch poisepms blob master sub 20menu png project search result search result screenshot https github com nadia jsch poisepms blob master search 20example png author nadia schmidtke email me https nadia jsch github io nadia schmidtke webpages contact html license this project is licensed under the gnu general public license https github com nadia jsch poisepms blob master license version history 2 0 this version data read and written to a local mysql database 1 0 https github com nadia jsch project management system first version the core functionality was achieved data was read and written to text files | java mysql-database project-management | server |
Courses-taken-to-revive-grow-my-tech-skillset | courses taken to grow my tech skillset i am on a journey of transitioning to cloud engineering and i m taking courses to not only grow me in this regard but to also rekindle my software engineering skills as such i will also be taking some ux ui and product management courses as these are areas i have experience amp interest in as well | cloud |
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ECC | ecc engineering cloud computing coursework assignments and projects | cloud |
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injoit-template | latex injoit latex international journal of open information technologies injoit http injoit ru ieeetran latex http www michaelshell org tex ieeetran pdflatex xelatex latex latex bash bibtex injoit rus xelatex injoit rus bibtex injoit rus xelatex injoit rus texstudio ide xelatex options configure texstudio build defualt compiler injoit rus tex | server |
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Knowledge-Hub | knowledge hub an information technology company | server |
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udagram | udagram image filtering microservice udagram is a simple cloud application developed alongside the udacity cloud engineering nanodegree it allows users to register and log into a web client post photos to the feed and process photos using an image filtering microservice the project is split into three parts 1 the simple frontend https github com udacity cloud developer tree master course 02 exercises udacity c2 frontend a basic ionic client web application which consumes the restapi backend covered in the course 2 the restapi backend https github com udacity cloud developer tree master course 02 exercises udacity c2 restapi a node express server which can be deployed to a cloud service covered in the course 3 the image filtering microservice https github com udacity cloud developer tree master course 02 project image filter starter code the final project for the course it is a node express application which runs a simple script to process images your assignment tasks beanstalk url filtered image http udagramsplitthoffdev us east 2 elasticbeanstalk com filteredimage image url https timedotcom files wordpress com 2019 03 kitten report jpg setup node environment you ll need to create a new node server open a new terminal within the project directory and run 1 initialize a new project npm i 2 run the development server with npm run dev create a new endpoint in the server ts file the starter code has a task for you to complete an endpoint in src server ts which uses query parameter to download an image from a public url filter the image and return the result we ve included a few helper functions to handle some of these concepts and we re importing it for you at the top of the src server ts file typescript import filterimagefromurl deletelocalfiles from util util deploying your system follow the process described in the course to eb init a new application and eb create a new environment to deploy your image filter service don t forget you can use eb deploy to push changes stand out optional refactor the course restapi if you re feeling up to it refactor the course restapi to make a request to your newly provisioned image server authentication prevent requests without valid authentication headers note if you choose to submit this make sure to add the token to the postman collection and export the postman collection file to your submission so we can review custom domain name add your own domain name and have it point to the running services try adding a subdomain name to point to the processing server note domain names are not included in aws free tier and will incur a cost | cloud |
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High-Level-Synthesis-Flow-on-Zynq-using-Vivado-HLS | high level synthesis flow on zynq using vivado hls this course provides professors with an understanding of high level synthesis design methodologies necessary to develop digital systems using vivado hls now under 2018 2 version source files setup to use the source files for each of the labs in this workshop you have to clone this repository from xup github for that do the following to be completed in the instructions for the labs sources lab source files you can download the source files for the labs from here https www xilinx com support university vivado vivado workshops vivado high level synthesis flow zynq html labs the actual lab contents labsolutions refers to here https www xilinx com support university vivado vivado workshops vivado high level synthesis flow zynq html this will require you to login into your xilinx account note board support for the pynq z1 z2 are not included in vivado 2018 2 by default the relevant files need to be extracted and saved to vivado installation data boards board files zynq these files can be downloaded from pynq z1 board files https www xilinx com support documentation university vivado workshops vivado adv embedded design zynq materials 2018x pynqz1 pynq z1 zip pynq z2 board files https www xilinx com support documentation university vivado workshops vivado adv embedded design zynq materials 2018x pynqz2 pynq z2 zip hardware setup pynq z1 z2 connect the board to the pc using a micro usb cable make sure that a jumper is connected to jtag between jp1 1 and jp1 2 to use the board in the development mode also make sure that another jumper is placed between j9 2 and j9 3 to select usb as a power source lab overviews lab1 this lab provides a basic introduction to high level synthesis using the vivado hls tool flow you will use vivado hls in gui mode to create a project you will simulate synthesize and implement the provided design lab2 this lab introduces various techniques and directives which can be used in vivado hls to improve design performance the design under consideration accepts an image in a custom rgb format converts it to the y uv color space applies a filter to the y uv image and converts it back to rgb lab3 this lab introduces various techniques and directives which can be used in vivado hls to improve design performance as well as area and resource utilization the design under consideration performs discrete cosine transformation dct on an 8x8 block of data lab4 this lab introduces a design flow to generate a ip xact adapter from a design using vivado hls and using the generated ip xact adapter in a processor system using ip integrator in vivado | os |
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Proof-of-Stake-Cryptocurrency-generator | proof of stake cryptocurrency generator github https img shields io github license mashape apistatus svg license telegram https img shields io badge chat telegram blue svg https t me coin generator medium badge https badgen net badge icon medium icon medium label https medium com sandoche twitter sandochee https img shields io twitter follow sandochee svg style social https twitter com sandochee create your own proof of stake cryptocurrency with its own blockchain based on nxt blockchain creation kit it should satisfy the requirements of the jelurida public license version 1 1 for the nxt public blockchain platform basically 10 of your tokens should be given to the owners of the nxt cryptocurrency furthermore the source needs to be disclosed and under the same license keep in mind that this generator is not perfect website https coingenerator sh read the story https medium com learning lab how to build your own cryptocurrency proof of stake in just a few minutes 6d526bca4a91 this generator will assist you building your nxt clone if you are an advanced user follow directly the official tutorial nxt clone starter https bitbucket org jelurida nxt clone starter introduction to the nxt blockchain creation kit https www youtube com watch v 6wg3uv07gu4 what are the cryptocurrency built with this generator motive https motive network meteor https github com minecraft meteor requirements java nodejs version 8 0 how to install java general java 8 ubuntu http www webupd8 org 2012 09 install oracle java 8 in ubuntu via ppa html debian http www webupd8 org 2014 03 how to install oracle java 8 in debian html freebsd pkg install openjdk8 how to install nodejs general https nodejs org en download video tutorial create your blockchain with that cryptocurrency https www youtube com watch v ww5izzb0wy french with english subtitle step 1 download the nxt blockchain and create the genesis block 1 clone this repository with git clone https github com sandoche proof of stake cryptocurrency generator also feel free to fork this repository 2 go to the cloned folder and install the npm dependencies with npm install 3 run the nxt blockchain with npm run nxt 4 then open http localhost 7876 index html in your favourite browser then create an account and save the private keys securely wait until the full blockchain is synced this can take a few hours copy your nxt address and also its public key 5 open the file docs config newgenesisaccounts json this file will define the repartition of the coins your are creating on the first block creation 1 billion of coins will be distributed 10 of them will be distributed to the nxt holders this is part of the jelurida public license you have to put the list of accounts you want to credit in the first block the genesis block and its matching public key the total of the amounts should be 90000000000000000 if you don t know what to do just put your nxt address your created step 1 4 and it s public key like this and save it if you are not sure about what you are doing check this video https www youtube com watch v 6wg3uv07gu4 balances my nxt address here 90000000000000000 publickeys the public key of this nxt address 6 go to http localhost 7876 test requesttag addons click on downloadjplsnapshot then upload your file newgenesisaccounts json and copy paste the height you can see in your wallet as in the screenshot below then submit a file will be generated after a few minutes save it as genesisaccounts json in the templates conf data folder screenshot docs assets height png 7 create another account like in step 1 4 and save its public address in the file templates conf data genesisparameter json also edit the epochbeginning with the current date step 2 create your own cryptocurrency 1 update the images from templates img according to your blockchain images and the favicon in templates 2 then just run npm run generate and answer the generator s questions the generator will automatically clone the nxt clone starter change the port and name in the source code for windows user you should use npm run generate docker and have docker installed 3 once the cryptocurrency generated you can of course edit the interface inside the yourcrypto html folder and find the java source in yourcrypto src java note that you can find many parameters that you can edit in the following file yourcrypto src java nxt constants java 4 run it go to yourcrypto folder compile with sh compile sh or win compile sh for windows then run with sh run sh or run bat for windows note that you can delete all the other folders they are now useless also you need to start forging yourself if you want to try to make transactions 5 find the api doc in the doc folder step 3 create the installer for the wallet optionnal in order to build please read the build documentation build readme md step 4 host your nodes in some servers once your cryptocurrency ready for deployement you need to host some nodes online these nodes will share the transactions with other nodes validates transactions and forge blocks you can do that in any virtual machine you can use for example amazon web services or ovh once you have your virtual machine here is how to do 1 connect to the machine i recommend ubuntu or debian 2 clone your cryptocurrency 3 install java 4 open as an inboud and outbound tcp port the peer port that you chose when you run the generator you can find it also in the yourcrypto src java nxt peer peers java as default peer port 5 run screen and run the node with sh run sh after sh compile sh 6 you now need to run the forging mode of your node in order to do that you can either do in command line following this do it also inside screen to let it forge curl d requesttype startforging d secretphrase passphrase http localhost port nxt don t forget of course to replace the port of the api port and the passphrase with the passphrase of an account that has enough effective balance to forge if the command line to launch forging does not work you can do it with the gui after installing a vnc server check the following links https medium com arafat graphical user interface using vnc with amazon ec2 instances 549d9c0969c5 https www digitalocean com community tutorials how to set up vnc server on debian 8 troubleshooting mac linux if step 1 doesn t work go to the nxt folder and run sh compile sh then sh run sh windows if step 1 doesn t work go to the nxt folder and run sh win compile sh then open run bat for step 2 you need to use docker so first install docker and then run npm run generate docker or docker run it rm name coin generator v pwd usr src app w usr src app node 8 npm run generate all os sometime when running the wallet it s not logging in open the wallet url in private navigation what is next you can find the source of the mobile app in the mobile folder show your support please this repository if this project helped you a href https www patreon com sandoche patreon png https c5 patreon com external logo become a patron button png https www patreon com sandoche a buy me a beer if you like this project feel free to donate bitcoin 19jinz1lkmaz57tewqjatg2hqwh4rgw4yp ethereum 0xded81fa4624e05339924355fe3504ba9587d5419 monero 43jqzmquw2q989uksrb2ybeffhmjhbyb2yxu289bv7plrh4xvgmkj5ytd52il6x1dvcys9erg5bihyxmjgkpsts6s2jmyjn motive motiv 25t5 sd65 v7lj bbwrd get motive now https motive network paypal https www paypal me kanbanote | nxt proof-of-stake generator cryptocurrency blockchain coin | blockchain |
blood_bank_app | blood bank app this is basicaly a software engineering project i have used firebase for the database and java as programing language login page img src loginpage jpeg width 280px alt screenshot menu page img src menupage jpeg width 280px alt screenshot donor info img src donorinfo jpeg width 280px alt screenshot check donor img src checkdonor jpeg width 280px alt screenshot bloodbank info img src bloodbankinfo jpeg width 280px alt screenshot srujanbannu blood bank app is licensed under the mozilla public license 2 0 | server |
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Mobile-Development-with-.NET-MAUI | mobile development with net maui mobile development with net maui by packt publishing | front_end |
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engineering-festival-iot-ui | engineering festival iot ui ui design for an embedded home automation system screenshot iot engfest https user images githubusercontent com 44490960 89357733 0c84f780 d6ca 11ea 9282 9698f8503ae6 png | os |
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IOT_vuln | iot vuln iot vuln | server |
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securitization_blockchain | implement asset securitization on a blockchain ledger in this code pattern we ll demonstrate how to simulate a securitization process using react js hyperledger fabric node sdk and an ibm blockchain service instance securitization is a financial process that can be used to consolidate a set of illiquid assets into a set of tradable securities a common example of an illiquid asset would be a home mortgage as they cannot be readily bought and sold an example of a tradable asset can be a stock or bond this process can be useful for financial institutions that are looking to increase the liquidity of their assets and free up capital this application provides a dashboard that will allow users to create and view the relationship between assets pools investors and securities when the reader has completed this code pattern they will understand how to deploy a hyperledger blockchain network on ibm cloud create and enroll a administrative client using the hyperledger node sdk deploy and instantiate a set of smart contracts to handle transactions and pool assets readme images arch flow securitization png flow 1 a homebuyer leverages the services of a loan originator to secure financing for a home mortgage 2 the loan originator loads the application and submits requests to update the blockchain ledger state with a new asset this request is handled by the node js express backend formats crud request into a jsonrpc http www jsonrpc org specification examples object like below and submits it to a hyperledger peer as a transaction proposal the request below would register a mortgage with a value of 540000 an interest rate of 3 3 and a credit score of 720 the credit score is used to calculate risk for potential investors json jsonrpc 2 0 method invoke params type 1 chaincodeid name securitization contracts ctormsg function init asset args asset1 540000 0 033 720 securecontext kkbankol us ibm com id 5 3 peer uses an endorsement service to simulate the proposed transaction against the relevant smart contracts this endorsement service is used to confirm that the transaction is possible given the current state of the ledger examples of invalid proposals might be creating an asset that already exists querying the state of an asset that does not exist etc 4 if the simulation is successful the proposal is then signed by the peer s endorser 5 the signed transaction is forwarded to an ordering service which executes the transaction in this case the newly created asset would be placed in an asset pool 6 the updated state is committed to the blockchain ledger 7 the securitization ui queries the updated ledger state and renders tables with the updated information 8 if the asset pool has been split up into securities an investor has the ability to buy and sell them the security price should be updated every time there is a change to the ledger state 9 a creditor checks the ledger state to determine the risk of losses by late payments or mortgages going into default if a significant change is found the security credit rating will be recalculated by the creditor and updated in the ledger install prerequisites ibm cloud cli to interact with the hosted offerings the ibm cloud cli will need to be installed beforehand the latest cli releases can be found at the link here https console bluemix net docs cli reference bluemix cli download cli html download install an install script is maintained at the mentioned link which can be executed with one of the following commands bash mac osx curl fssl https clis ng bluemix net install osx sh linux curl fssl https clis ng bluemix net install linux sh powershell iex new object net webclient downloadstring https clis ng bluemix net install powershell after installation is complete confirm the cli is working by printing the version like so bash ibmcloud v bash log in ibmcloud login finally install the container service plugin which is required to interact with ibm kubernetes deployments bash ibmcloud plugin install container service r bluemix kubernetes cli bash os x curl https storage googleapis com kubernetes release release v1 11 7 bin darwin amd64 kubectl p usr local bin linux curl https storage googleapis com kubernetes release release v1 11 7 bin linux amd64 kubectl p usr local bin chmod x usr local bin kubectl kubectl v windows curl https storage googleapis com kubernetes release release v1 11 7 bin windows amd64 kubectl exe node js packages if expecting to run this application locally please install node js https nodejs org en and npm currently the hyperledger fabric sdk only appears to work with node v8 9 0 but is not yet supported https github com hyperledger fabric sdk node build and test on node v9 0 if your system requires newer versions of node for other projects we d suggest using nvm https github com creationix nvm to easily switch between node versions we did so with the following commands bash curl o https raw githubusercontent com creationix nvm v0 33 11 install sh bash place next three lines in bash profile export nvm dir home nvm s nvm dir nvm sh nvm dir nvm sh this loads nvm s nvm dir bash completion nvm dir bash completion this loads nvm bash completion nvm install v8 9 0 nvm use 8 9 0 to run the securitization ui locally we ll need to install a few node libraries which are listed in our package json file react js https reactjs org used to simplify the generation of front end components mqtt http mqtt org client package to subscribe to watson iot platform and handle incoming messages hyperledger fabric sdk https fabric sdk node github io enables backend to connect to ibm blockchain service included components ibm blockchain https console bluemix net catalog services blockchain featured technologies hyperledger fabric https hyperledger fabric readthedocs io en release 1 1 hyperledger node js sdk https github com hyperledger fabric sdk node npm https www npmjs com node js https nodejs org en react js https reactjs org steps there are two methods we can use to deploy the application either run everything locally on your development machine or initialize a hosted blockchain service and run in ibm cloud these separate steps are labeled as local or hosted respectively 1 clone repository 1 clone the repository 2 provision blockchain kubernetes services in ibm cloud platform 2 provision cloud services 3 configure ibm cloud services 3 configure ibm cloud services 5 start the application 5 run the application 4 configure and deploy application locally 4 deploy application locally or on ibm cloud 4 deploy application on ibm cloud 5 import service credentials 5 import service credentials 6 configure application 6 populate application data 7 configure and run the application 7 ui configuration 1 clone the repository clone the securitization blockchain project locally in a terminal run bash git clone https github com ibm securitization blockchain git 2 provision cloud services hosted next we ll need to deploy our service instances using the ibm cloud dashboard this step is only required if you re using a hosted blockchain service instead of a local hyperledger network blockchain the ibm blockchain service can be found by logging in to the ibm cloud dashboard https console bluemix net selecting the catalog button searching for blockchain and clicking on the resulting icon or click this link https console bluemix net catalog services blockchain img src https i imgur com qwqoxq5 png after selecting the blockchain icon a form will be presented for configuring the service name region and pricing plan the default values for these fields can be left as is after validating that the information in the form is correct scroll down and click the create button in the lower right corner img src https i imgur com roajozr png kubernetes create a kubernetes cluster here https console bluemix net containers kubernetes catalog cluster create the free offering will suffice for this demo app kubernetes will be used to deploy a ubuntu container running the express and react applications todo add photos img src https i imgur com ees7kab png run the following command to download the configuration file for your cluster the mycluster parameter is the default cluster name as seen in above screenshot be sure to change this parameter if you entered a custom cluster name bash ibmcloud cs cluster config mycluster the result of the previous command will download a configuration file which will be used to connect to the container service the output will contain an export command like so export kubeconfig users user bluemix plugins container service clusters mycluster kube config hou02 mycluster yml after running the command above confirm that the kubernetes cli can communicate with the container service by running the following bash kubectl get nodes provision the following services ibm blockchain https console bluemix net catalog services blockchain watson iot platform https console bluemix net catalog services internet of things platform 3 configure ibm cloud services in this section we ll be uploading our securitization logic to the blockchain service smart contracts commonly referred to as chaincode can be used to execute business logic and validate incoming requests in this context the contracts are used to initialize all participants of the securitization process define their relationships and verify transactions these contracts can be hosted either on ibm cloud or on a local hyperledger network managed by docker ibm cloud hosted hyperledger hosted to begin the process of uploading the smart contracts also referred to as chaincode to the hosted blockchain service we can start by opening the ibm cloud dashboard selecting your provisioned blockchain service and accessing the blockchain network monitor by clicking enter monitor img src https i imgur com bpujphe png next click the install code option on the left hand menu and then the install chaincode button on the right of the page img src https i imgur com hmddsgm png enter an id and a version here we ll use sec and v1 then select the choose files button to upload the smart contracts which are titled lib go chaincode src lib go read ledger go chaincode src read ledger go write ledger go chaincode src write ledger go and securitization go chaincode src securitization go these files are located in the chaincode src directory of this project img src https i imgur com njgmwpm png finally we ll need to instantiate the chaincode this can be done by opening the chaincode actions menu and selecting instantiate this will present a form where arguments can be provided to the chaincode init function in this case we ll just need to provide an integer we used 101 to the arguments section then click next and then submit img src https i imgur com eh1djmj png hyperledger network setup local if you re planning to make custom changes to the smart contracts it may be faster to develop and test chaincode locally before pushing to a hosted service as an alternative to the hosted ibm blockchain service we can deploy a local hyperledger network using docker compose in a script like so enter the local directory bash cd local run the stopfabric script to clean up by removing any residual hyperledger containers this will also remove the securitization container if it exists bash stopfabric sh start a new hyperledger network bash export compose project name net startfabric sh the network can be deleted at any time by running stopfabric sh next run the the installchaincode sh local installchaincode sh script which will installs and instantiates the smart contracts on the hyperledger network installchaincode sh next copy the chaincode artifacts to the docker cli container docker cp chaincode src cli opt gopath src github com securitization now we can run a series of docker commands to install and instantiate the chaincode from the cli container first we ll install the chaincode docker exec e core peer localmspid org1msp e core peer mspconfigpath opt gopath src github com hyperledger fabric peer crypto peerorganizations org1 example com users admin org1 example com msp cli peer chaincode install n securitization v 1 0 p github com securitization and instantiate the chaincode docker exec e core peer localmspid org1msp e core peer mspconfigpath opt gopath src github com hyperledger fabric peer crypto peerorganizations org1 example com users admin org1 example com msp cli peer chaincode instantiate o orderer example com 7050 c mychannel n securitization v 1 0 c args 101 once this is complete we can invoke smart contracts using docker exec like below this invoke call runs the read everything function which prints all assets securities etc docker exec e core peer localmspid org1msp e core peer mspconfigpath opt gopath src github com hyperledger fabric peer crypto peerorganizations org1 example com users admin org1 example com msp cli peer chaincode invoke o orderer example com 7050 c mychannel n securitization c args read everything 4 deploy application on ibm cloud hosted deploy to ibm cloud https bluemix net deploy button png https bluemix net deploy repository https github com ibm securitization blockchain git branch master 1 we can deploy the application to ibm cloud by either leveraging the deploy to ibm cloud button directly above or by using the ibm cloud cli ensure the cli is installed using the prerequisites section above and then run the following command to deploy the application before running this section please confirm that the bash log in using ibm cloud credentials ibmcloud login deploy the kubernetes application with the following command bash kubectl apply f kubernetes kube config yml if successful you should get the following output bash kalonjis macbook pro securitization blockchain kkbankol us ibm com kubectl apply f kubernetes kube config yml service api service created pod securitization pod created this may take a few minutes in a different tab folloing along by running the logs command like so bash kubectl logs f securitization pod we should get output saying the backend and react servers have started continue on to access the application to access the pod filesystem run the following commands kubectl get pods kubectl exec it pod name bash find the public ip address of the kubernetes cluster bash get id of cluster if it s not the default mycluster ibmcloud ks clusters print workers associated with cluster take note of public ip ibmcloud ks workers mycluster confirm that the node js application is up and running by opening the following worker public ip 30000 4 deploy application locally local both python2 7 and build essential are required for these dependencies to install properly please refer to the install deps sh script if installing on a new system install dependencies for local application deployment continue by installing node js https nodejs org en runtime and npm currently the hyperledger fabric sdk only appears to work with node v8 9 0 but is not yet supported https github com hyperledger fabric sdk node build and test on node v9 0 if your system requires newer versions of node for other projects we d suggest using nvm https github com creationix nvm to easily switch between node versions we can install nvm and node v8 9 0 with the following commands curl o https raw githubusercontent com creationix nvm v0 33 11 install sh bash place next three lines in bash profile export nvm dir home nvm s nvm dir nvm sh nvm dir nvm sh this loads nvm s nvm dir bash completion nvm dir bash completion this loads nvm bash completion nvm install v8 9 0 nvm use 8 9 0 install the required node packages by running npm install in the sc ui directory and in the sc ui react backend directory both python and build essential are required for these dependencies to install properly bash install react dependencies cd sc ui npm install install express hyperledger dependencies cd react backend npm install return to the root project directory cd add the following entries to the etc hosts file this is only necessary when running the app locally and routes the url for each hyperledger component to localhost 127 0 0 1 peer0 org1 example com 127 0 0 1 ca example com 127 0 0 1 orderer example com finally run the application cd sc ui port 30000 npm start port 30001 deploy type local node react backend bin www docker setup local alternative if you have docker installed you can install these dependencies in a virtual container instead run the application with the following commands and then skip to step 5 5 configure credentials build the application and dependencies in a docker image like so bash docker build t securitization blockchain then start the docker container with docker run it p 30000 30000 p 30001 30001 name securitization e deploy type local network net basic securitization blockchain bash c cd root securitization blockchain sc ui port 30000 npm start port 30001 node react backend bin www the application can instead be booted from a public image as well if there is no need to build a custom image docker run it p 30000 30000 p 30001 30001 name securitization e deploy type local network net basic kkbankol securitization blockchain bash c cd root securitization blockchain sc ui port 30000 npm start port 30001 node react backend bin www this method is ideal for a development environment but not suitable for a production environment todo this comment is from the original author would like to understand why to access the local securitization application open the following url in a browser http localhost 30000 add a section that explains to the reader what typical output looks like include screenshots todo update dashboard view img src https i imgur com nljtwdf png include any troubleshooting tips driver issues etc 5 import service credentials hosted this section is only necessary for working on the hosted ibm cloud blockchain offering if deploying locally you can skip to step 7 the credentials for ibm cloud blockchain service can be found in the services menu in ibm cloud by selecting the service credentials option for each service if using the local network the blockchain credentials consist of the key secret and network id parameters https i imgur com qof7sve png width 250 height 400 img src https i imgur com qof7sve png we ll also need to provide the chaincode id and version which is sec and v1 in this example the credentials will need to be entered in the configuration form which can be opened by clicking the button in the upper right of the ui img src https i imgur com zsxkxha png after submitting this form the ui will fetch a connection profile json file which contains all information needed by our hyperledger client to connect to the blockchain ledger once the connection profile has been retrieved a certificate will be generated to allow the application to make administrative requests these elevated privileges are required to make calls to the chaincode service this pem encoded certificate will be output in the terminal logs like so if deploying on ibm cloud this certificate can be found parsing the logs using kubectl logs f securitization pod or by opening the developer console in your browser img src https i imgur com z6wmx59 png once the pem certificate is generated it can be copied and uploaded by visiting the printed url or by revisiting the blockchain monitor navigating to members on the left hand menu and then clicking certificates and add certificate img src https i imgur com kx654re png these credentials will need to be provided to the ui in the next step we can obtain the blockchain credentials by downloading copy the env sample env sample to env cp env sample env edit the env file with the necessary settings env sample replace the credentials here with your own rename this file to env before starting the app watson conversation conversation username add conversation username conversation password add conversation password workspace id add conversation workspace watson discovery discovery username add discovery username discovery password add discovery password discovery environment id add discovery environment discovery collection id add discovery collection watson natural language understanding natural language understanding username add nlu username natural language understanding password add nlu password watson tone analyzer tone analyzer username add tone analyzer username tone analyzer password add tone analyzer password run locally on a non default port default is 3000 port 3000 6 configure application todo reword this the securitization flow generally occurs in the following format 1 a homebuyer will apply for financing of an asset via a loan originator the loan will have a balance interest rate monthly payment and expected time period for payback many mortgages are roughly 30 years a total expected payoff amount will be generated based off this information as well 2 once the loan has been approved and processed the loan originator then finances the asset and transfers the debt to a special purpose vehicle which is a entity that protects the assets even if the originator goes bankrupt 3 the asset is then placed into a pool along with other assets once assets have been placed into a pool a set of securities can be generated to allow the pool to become tradable each security can be bought and sold by investors and has a yield which determines the return each security holder will receive on their investment 4 the homebuyer submits payments towards their mortgage 5 each payment is split up and distributed amongst investors who own securities associated with the pool when all mortgages in the pool are paid off each investor should have received their original investment back plus the agreed yield amount each payment will also have a processing fee which will be dispersed to the originator this securitization process can be replicated with this application by visiting the dashboard and creating originators assets pools securities and investors using the provided forms each form requests an unique id where the format is the name of the object type asset investor followed by an integer for example an asset will need an id like asset1 and asset pool needs an id like pool123 and a security needs an id like security15 first we ll need to create a loan originator which will require an id processing fee percentage and optional company name this form can be loaded by selecting the create originator button note there is a known intermittent issue with this originator creation process so the initial submission may fail if this occurs please try submitting again img src https i imgur com grnqtyh png img src https i imgur com qkgzhrj png note that the balance and assets fields in the table are initially blank but will be filled in as we associate assets with the originator and as the originator receives processing fees and security sale proceeds their balance will increase as well next we ll create an asset which will require an outstanding balance interest rate and a payment period which defines how many monthly payments they ll need to pay off their entire balance this can be done by scrolling directly down to the assets table clicking the create new asset button img src https i imgur com bg8jmsq png once the asset has been created we can also link it to an originator using the transfer asset button img src https i imgur com n6phrsr png the resulting table should then reflect the following img src https i imgur com icd3qt9 png create an asset pool via the create pool form by providing an id we can also transfer our asset s to the pool using the transfer asset button in the assets table create one or more securities the create security form will require a id associated asset pool and coupon rate the coupon rate defines the return on investment finally we can create our investors which have the ability to buy and sell securities this can be done by clicking the create investor button and providing a unique id once the investor is created we can then buy and sell securities using the respective buttons so in this example we ll do so by clicking the buy security button and providing the security and investor id now we can simulate a mortgage payment and view the corresponding payment distributions we can do so by scrolling back up to the assets table selecting the process payment view and entering an asset id and payment amount img src https i imgur com vndtcsl png submitting the payment will then calculate the payment amount allocated to interest and principal adjust the remaining balance calculate and disperse payment amount owed to security holders and originator place remainder in excess spread once these calculations are complete the dashboard tables will then be updated with the latest ledger state img src https i imgur com nljtwdf png troubleshooting sendpeersproposal promise is rejected error 2 unknown chaincode error status 500 message authorization for getinstalledchaincodes on channel getinstalledchaincodes has been denied with error failed verifying that proposal s creator satisfies local msp principal during channelless check policy with policy admins this identity is not an admin this error occurs if the certificate generated by the sdk user has not been uploaded to the peer error the grpc binary module was not installed this may be fixed by running npm rebuild grpc is a requirement for the fabric client sdk confirm that it has been installed in the react backend directory with npm install grpc 1 11 0 error client utils js sendpeersproposal promise is rejected error 2 unknown chaincode error status 500 message authorization for getinstalledchaincodes on channel getinstalledchaincodes has been denied with error failed verifying that proposal s creator satisfies local msp principal during channelless check policy with policy admins this identity is not an admin this error occurs if the admin certificate for the hosted ibm blockchain service has not been uploaded objects are not valid as a react child this error occurs if one of the golang structs defined in the chaincode are invalid these may not have nested objects to fix this clear cookies or open a different browser error environment guid is still not active retry once status is active this is common during the first run the app tries to start before the discovery environment is fully created allow a minute or two to pass the environment should be usable on restart if you used deploy to ibm cloud the restart should be automatic error only one free environment is allowed per organization to work with a free trial a small free discovery environment is created if you already have a discovery environment this will fail if you are not using discovery check for an old service thay you may want to delete otherwise use the env discovery environment id to tell the app which environment you want it to use a collection will be created in this environment using the default configuration this can stay as is if using deploy to ibm cloud include any relevant links links pick the relevant ones from below learn more blockchain patterns enjoyed this code pattern check out our other blockchain patterns https developer ibm com code technologies blockchain 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 https www apache org licenses license 2 0 txt apache software license asl faq https www apache org foundation license faq html whatdoesitmean | blockchain |
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engapp-mdp | engapp mobile development pattern pref cio seja bem vindo a esta documenta o nela vamos exibir como n s desenvolvedores mobile da engapp organizamos criamos e montamos nossos softwares utilizando o flutter http flutter dev flutter exibiremos nosso guia de boas pr ticas para padronizar nosso desenvolvimento e consequentemente espalhar para os que ainda n o tenham um rumo ou est o come ando nessa rea e querem um norte para tal ent o vamos l introdu o se voc chegou at esse documento porque desenvolve software para mobile usando especificamente o flutter que nossa stack oficial para tal ent o vamos come ar vamos passar pelos seguintes t picos estrutura do projeto diferen a entre fun es e classes e como escrever as mesmas declaracao de variaveis gerenciamento de estado obs essa documenta o aqui ser nossa base inicial nada impede que ela seja alterada conforme fomos descobrimos maneiras mais f ceis melhores de fazer o que fazemos atualmente obs 2 caso voc tenha um outro padr o para organizar n o se prenda a este conte do aqui voc ir encontrar como a eng app organiza e por fim padroniza seus projetos estrutura do projeto quando se fala em estrutura do projeto quero dizer como organizar seus arquivos suas pastas sub pastas sub arquivos enfim como seu projeto dever se organizar daqui pra frente segue exemplo pastas folder https i imgur com mbv52nu png sempre vamos iniciar dentro da pasta lib com a pasta src dentro dela seguimos com a cria o de nossos componentes criando a pasta components dentro teremos por exemplo a login component e dentro de cada algum componente teremos sua pasta de utils com o arquivo nome do componente pricipal utils dart assim como nosso arquivo para gerenciar nossos requests de api no nosso arquivo de utils vamos separar nossos componentes widgets do componente principal segue exemplo componentes componente https i imgur com tv23fjw png componente com isso mantemos nosso c digo limpo e conciso e no componente utils referente ao principal estar o nossos widgets desenvolvidos no nosso arquivo de network onde ficar o todas as conex es necess rias daquele componente por exemplo no network login dart teremos apenas a requisi o para fazer o login e assim por diante com os demais componentes do projeto fun o classe ou vari vel local como voc j deve saber existem diversas maneiras de se declarar um componente no flutter esses 3 tipos s o os mais utilizados fun o classe e vari vel local nenhum dos 3 est errado todos executam de maneira correta o que o usu rio digitou por m diversos jeitos de se declarar a mesma coisa pode ficar confuso e at mesmo de dif cil manuten o futuramente tanto para voc como para outro programador que venha pegar seu c digo vamos a alguns exemplos fun o widget functionwidget widget child return container child child classe class classwidget extends statelesswidget final widget child const classwidget key key this child super key key override widget build buildcontext context return container child child percebemos aqui que ambas fazem o que foi solicitado eles criam um container e chamam um child como widget filho no papel o que ocorre exatamente isso por m o framework desconhece fun es mas reconhece classes nossa rvore de widgets ficaria assim no primeiro exemplo container container e no segundo classwidget container classwidget container e isso faz uma diferen a enorme em rela o a como o framework se comporta quando temos que atualizar um componente aqui est uma lista de itens comparando o uso de fun es com classe 1 classes otimiza o na performance const constructor operator override rebuild mais granular possuem hot reload podemos v las no widget inspector debugfillproperties podemos atribuir chaves podemos usar seu pr prio contexto garantem que todos os widgets s o usados da mesma forma garantem que se trocarmos entre dois layouts diferentes o m todo dispose vai funcionar corretamente e ir liberar os recursos as fun es geralmente utilizam estado anterior 2 fun es possuem menos c digo podemos ver claramente e com mais detalhe agora n o estamos proibindo o uso de fun es por m para declarar componentes visuais temos a prefer ncia e ser sempre nossa escolha n mero 1 o uso de classes utilizamos fun es para declarar m todos como de requisi es alguma verifica o entre outros obs n o recomendamos o uso de declarar vari veis locais por n o ser t o leg vel quanto uma classe quando se vai observar um c digo vari veis j vimos at ent o a nossa recomenda o para estruturar seu projeto e como criar da melhor forma seus componentes widgets outro assunto bastante importante no tocante a como devemos declarar nossas vari veis sejam elas simples como declarar um inteiro ou string seja ao nomear suas fun es e at mesmo suas classes como j dizia robert c martin autor do livro codigo limpo https www amazon com br c digo limpo habilidades pr ticas software dp 8576082675 codigo limpo declara que devemos pensar bem no nome de nossas vari veis n o importa se vamos demorar ou n o para dar um nome mas esse nome tem que ser o mais claro e de prefer ncia que d significado ao que voc quer que execute seguindo claro o princ pio da responsabilidade nica no qual aquela classe aquela fun o vai executar apenas uma nica tarefa e nada al m disso vamos a alguns exemplos ao decorrer da nossa jornada j vimos v rios exemplos de vari veis como esse daqui var x at ent o pra quem est criando o c digo pode ser at que n o veja tanto problema essa vari vel com o nome x afinal ele mesmo est sabendo como utilizar ela seja para armazenar algum inteiro uma string no entanto conforme o tempo vai passando voc come a a desenvolver mais seu projeto e acaba esquecendo aquela vari vel x futuramente quando se necess rio dar a manuten o voc possivelmente vai ficar perdido tentando descobrir o que aquela vari vel x est fazendo ali e qual seu uso isso algo que robert c martin e n s da engapp reprovamos consideramos isso como bad practice jamais em hip tese alguma permitiremos o uso de vari veis desse tipo o c digo que devemos escrever a nossa comunica o com outros profissionais se futuro programador ou ate mesmo voce nao entender o que est acontecendo com seu c digo como voc poder cuidar dele at mesmo entender ele imposs vel dessa maneira sempre h um por m esse por m se d caso sua aplica o seja pra mostrar algo r pido pro cliente ou at mesmo pra vc ver como est sua aplica o se seu projeto estiver tomando maiores propor es crescendo cada vez tira um dia livre para refatorar essas vari veis voc pode at achar que perda de tempo fazer isso tudo bem opini o sua mas torca entao pra nao ter que dar manuten o no seu c digo futuramente | front_end |
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blockchain-on-nodejs | blockchain on nodejs node js 2 3 node js 3 0 node js pr 1 100 2019 9 7 imfly log x 2020 2 15 ddn ddn 3 ddn md x 2020 1 28 ddn ddn 2 ddn md x 2020 1 24 ddn 1 md x 2019 11 19 https www bilibili com video av76296940 x 2019 11 11 0 md ddn http mainnet ddn link ddn http wallet ddn link ddn https www ddn link product wallet github issue datm ddnlink ddn issues https github com ddnlink ddn issues img src styles images datm ddn jpeg alt width 100px ps datm ddn ddn ddn http wallet ddn link ddn https www ddn link product wallet ddn ddn ddn ddn dljrrvwnmmxstcayvjcrpwyyb3ky1ehabu styles images foundation png contributors imfly 3 0 cc by nc nd 3 0 http creativecommons org licenses by nc nd 3 0 deed zh | blockchain |
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foodie | foodie food delivery app mobile food delivery app developed with react native and expo for the final project of coderhouse mobile development course in it you can register or log in to order food search for restaurants by name or type add restaurants to your favorite list manage your order manage your directions and credit debit cards manage your profile upload a profile picture among many other things design https user images githubusercontent com 42822912 223870265 7caaa53c a816 4f9e a250 0133dc7d9855 jpg features 1 authentication users can register and login himselfs 2 order food users can make orders to any of the restaurants that foodie offers 3 search and filter restaurants and food users can filter restaurants and food by searching the name or filtering by tags 4 favorite restaurants users can add restaurants as favorites so they can make orders quickly 5 checkout options users can increase decrease or delete items from the order and they can choose the payment method 6 orders history users can see their history of orders and more details about an specific order 7 user information users can see their information and edit it 8 avatar photo users can upload an avatar photo from their library or with the camera 9 addresses and cards users can add and manage their addresses and cards app demo authentication and profile management flow https user images githubusercontent com 42822912 223637844 a84557d1 08d9 4c7c b431 f72289ca4e2d mov food ordering and orders history flow https user images githubusercontent com 42822912 223637748 34c1fe47 4d85 4154 adc7 604f524f6d51 mov architecture and data model foodie uses firebase as a cloud service for persistence authentication and storage of multimedia content foodie data model https user images githubusercontent com 42822912 223870326 589a13cf 1513 44a1 af98 97bcc4e20062 jpg data model foodie architecture https user images githubusercontent com 42822912 223870337 e8b33e34 a5a3 4757 88ed d6d6e615808b jpg architecture app technical information foodie is developed with react native and expo global state management global application state is managed with redux toolkit this is responsible for managing the authentication status of the app the user s current order order history and addresses and the available restaurants authentication the application uses firebase as an external authentication layer navigation the navigation of the app can be separated into authentication and application when there is no logged in user the application shows the authentication stack on the other hand when there is a logged in user the navigation tab is shown consisting of 3 tabs food orders and profile where each of these is a separate stack sqlite the application connects with the sqlite database to obtain and store the addresses of the users device camera and library the camera and gallery of the device are used so that users can change their profile picture personal data visit my github https github com mathiramilo profile to see more amazing projects if you are interested contact me on linkedin https www linkedin com in mathias ramilo | food-delivery-application mobile react-native firebase expo redux-toolkit | front_end |
blockchain-fastapi | blockchain fastapi mine block get the entire blockchain get the last mined block validate the blockchain | blockchain |
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pbp0 | website this website is built using docusaurus 2 https docusaurus io a modern static website generator installation yarn local development yarn start this command starts a local development server and opens up a browser window most changes are reflected live without having to restart the server build yarn build this command generates static content into the build directory and can be served using any static contents hosting service deployment using ssh use ssh true yarn deploy not using ssh git user your github username yarn deploy if you are using github pages for hosting this command is a convenient way to build the website and push to the gh pages branch | front_end |
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meta_course | meta course database engineering first repository | server |
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QtMobileApp | b followng features are implemented b 1 stackview 2 drawer 3 header 4 moving back to prevous screen 5 resolving html file and display in webview 6 resolving network url using qnetworkaccessmanager can access webservice 7 handling error condition b pending features b 1 scaling of imgaes based on dpi | qml qt5 qtquick mobile-app cross-platform android-application ios-app | server |
cryptography | preface readme md history readme md encrypttype readme md hash readme md blockcipher readme md mac readme md pki pki readme md digitalsignature readme md share readme md mpc mpc readme md ot readme md gc readme md mpc mpc mpc implementation md zkp zkp introduce md zkp app md groth16 zkp groth16 md sonic fractal halo supersonic marlin plonk zk stark china readme md preface readme md v1 0 1 guoshijiang2012 163 com lgzaxe discord https discord gg ww86tqew telegram shijiangguo twitter seek web3 eth 0xe3b4ecd2ec88026f84cf17fef8babfd9184c94f0 erc20 0xe3b4ecd2ec88026f84cf17fef8babfd9184c94f0 layer2 0xe3b4ecd2ec88026f84cf17fef8babfd9184c94f0 savourlabs savourdao python go rust node vue react guoshijiang2012 163 com lgzaxe discord https discord gg ww86tqew telegram shijiangguo twitter seek web3 | cryptography blockchain | blockchain |
Prism | p align center img src assets gh logo jpg alt prism design system code generator logo title prism design system code generator logo br a href https actions badge atrox dev gettengineering prism goto target blank alt build status title build status img src https github com gettengineering prism workflows prism badge svg branch main alt build status title build status a a href https codecov io gh gettengineering prism target blank alt code coverage for prism on codecov title code coverage for prism on codecov img src https codecov io gh gettengineering prism branch main graph badge svg alt code coverage for prism on codecov title code coverage for prism on codecov a img src https img shields io badge platform macos 20 7c 20linux 23989898 a href https github com apple swift package manager img src https img shields io badge spm compatible brightgreen svg alt swift package manager support a p prism is a design system code generator developed by the team at gett synchronizing design teams with engineering teams is a huge challenge as teams scale new growing pains start around how to properly align colors text styles spacing and other design details between teams in a uniform way from a single source of truth prism was built to solve this very problem it takes either zeplin project styleguide or a set of figma files as input and generates any output code you want from these based on a set of templates in your project resulting in cross platform code that is always synchronized from a single source of truth your design files prism is especially useful when used in your ci cd process to remove the friction of design handoff and review and making sure all of your teams are properly synchronized in regards to naming values and more getting started videos a 60 seconds introduction to prism https www youtube com watch v mncaauji yy design a design system swift heroes italy https www youtube com watch v ufyx7etbcmu 25 minutes getting prism there are five options to install prism 1 install with homebrew https brew sh brew install gettengineering tap prism 1 install using mint https github com yonaskolb mint mint install gettengineering prism 1 build from source make install 1 run directly with spm swift run prism generate 1 running on windows running on windows experimental experimental getting a provider api token figma to use prism with figma you ll need to generate a personal access token jwt to figma s api by going to https www figma com https www figma com then go the settings section under your profile finding the settings section in figma assets gh figma pat1 png finding the settings section in figma scroll to the bottom of the account tab find the personal access tokens section and create your new token generating a figma personal access token assets gh figma pat2 png generating a figma personal access token you ll need to expose this token to run the prism cli tool make sure you have a figma token environment variable with your token configured when running prism in a ci environemnt we recommend adding figma token as an environment secret when using prism locally or bootstrapping your project for the first time you can simply run export figma token zeplin personal token before running prism locally zeplin to use prism with zeplin you ll need to generate a personal access token jwt to zeplin s api by going to https app zeplin io profile developer https app zeplin io profile developer and click the create new token button in the personal access tokens section generating a zeplin personal access token assets gh zeplin pat png generating a zeplin personal access token you ll need to expose this token to run the prism cli tool make sure you have a zeplin token environment variable with your token configured when running prism in a ci environemnt we recommend adding zeplin token as an environment secret when using prism locally or bootstrapping your project for the first time you can simply run export zeplin token zeplin personal token before running prism locally bootstrap prism for your project inside your project folder run prism init it will guide you through selecting a zeplin project styleguide or a set of figma files as source along with other useful information for proper code generation once prism init is successful you ll find a new prism folder with a config yml file outlining your preferences creating templates prism uses templates with the prism suffix located in your project s prism folder these prism templates are basically plain text files prism doesn t really care what format or language you use it can make any kind of output as long as you can express it in a prism template file prism looks for something called tokens documentation tokens md inside your templates these tokens follow the following format token you can find a couple of sample templates in the examples https github com gtforge prism tree main examples folder here are two short example of generating colors code for ios and android using prism templates colors swift prism color swift ios prism template assets gh colors ios gif color swift ios prism template colors xml prism color swift android prism template assets gh colors android gif color swift android prism template development run make or make install to build a release binary of the prism cli tool and install it to usr local bin run make build to build a release binary of the prism cli tool run make project to create an xcode project and start working run make test to run all tests run make clean to clear the generated xcode project | design-system swift codegen zeplin design-tools tooling design design-systems design-system-manager designops hacktoberfest | os |
CoinExchange_CryptoExchange_Java | crypto exchange coin exchange maybe the best open source core code exchange in the entire net the architecture code quality is visible i think this may be the best choice for you to build an exchange or secondary development statement 1 i have been working in the new company i will take the time to update some descriptive things here so that everyone can compile build and develop statement 2 the app source code and the trading robot source code are not open source provided for a fee if necessary email 837385225 qq com i am a chinese so chinese is my mother language but i can also use both english and japanese to communicate with you introduction this project is a bitcoin exchange based on java springcloud btc exchange eth exchange digital currency exchange trading platform matching trading engine this project is based on the development of spring cloud microservices which can be used to build and secondary development digital currency exchanges and has a complete system component match trading engine background management back end front end frontend transaction page event page personal center etc native android app source code native apple app source code currency wallet rpc source code multi language support simple chinese english pc https images gitee com uploads images 2020 0422 182754 a150e134 2182501 png qq 20200422182717 png app https images gitee com uploads images 2020 0422 182544 05863aa2 2182501 png 1 png app https images gitee com uploads images 2020 0422 182559 860d3c60 2182501 png 2 png system architecture overview just draw a few sketches just look at it overall structure https hashcome cos 1251041754 cos ap hongkong myqcloud com githubimages overall 20structure png 1 png logical architecture https hashcome cos 1251041754 cos ap hongkong myqcloud com githubimages architect 2 png 2 png deployment architecture https hashcome cos 1251041754 cos ap hongkong myqcloud com githubimages deployment 20architecture png 1117 png dependencies https hashcome cos 1251041754 cos ap hongkong myqcloud com githubimages dependencies png qq 20200407194419 png system demonstration video pc front end user web end https gitee com cexchange coinexchange attach files https gitee com cexchange coinexchange attach files mobile app https gitee com cexchange coinexchange attach files https gitee com cexchange coinexchange attach files management background https gitee com cexchange coinexchange attach files https gitee com cexchange coinexchange attach files development reference development reference document https gitee com cexchange coinexchange blob master develop md https gitee com cexchange coinexchange blob master develop md manage background screenshots https gitee com cexchange coinexchange tree master 09 doc https gitee com cexchange coinexchange tree master 09 doc e7 ae a1 e7 90 86 e5 90 8e e5 8f b0 e8 bf 90 e8 a1 8c e6 88 aa e5 9b be about server configuration and deployment if you want to build an exchange system on your computer or cloud server i have prepared some basic deployment manuals of course installing software on linux unix is not a simple matter you need to have a certain linux basics and command line skills but also the courage and patience to solve problems i wish you success server configuration reference manual 09 doc 00 md installation basic environment manual 09 doc 00 md service deployment script 09 doc 00 install sh install mysql manual 09 doc 00 mysql md install redis manual 09 doc 00 redis md install zookeeper manual 09 doc 00 zookeeper md install kafka manual 09 doc 00 kafka md nstall mongodb manual 09 doc 00 mongodb md building a btc wallet node manual 09 doc 00 btc md building eth wallet node manual 09 doc 00 eth md manual of building usdt wallet node 09 doc 00 usdt md about springcloud spring cloud is an ordered collection of frameworks it uses spring boot s development convenience to subtly simplify the development of distributed system infrastructure such as service discovery registration configuration center message bus load balancing circuit breaker data monitoring etc can be done using spring boot s development style one click to start and deploy spring cloud does not repeat the manufacturing of wheels it just combines the mature and practical service frameworks developed by various companies the re encapsulation through the spring boot style shields the complex configuration and implementation principles and finally gives the development the author has left a set of distributed system development kits that are simple to understand easy to deploy and easy to maintain in general a complete spring cloud framework should be as shown in the following figure springcloud https images gitee com uploads images 2020 0408 133052 3ec984df 2182501 png 2 png if you are unfamiliar with spring cloud you can simply learn about spring cloud related tutorials first so that you will come back to this project and it will be easier to get started as a reminder because the springcloud framework diagram is a complete architecture we will tailor some content appropriately during development to make development and deployment faster so there are some discrepancies about matchmaking trading engine the system uses memory matching for the transaction queue kafka is used for matching order information transmission mongodb persists the order transaction details and mysql records the overall order transaction among them the 01 framework exchange project is mainly responsible for memory matching and the 01 framework market project is mainly responsible for order transaction persistence market generation market push and other services including k line data the intervals are 1 minute 5 minutes 15 minutes 30 minutes 1 hour 1 day 1 week 1 month market depth data for all trading pairs the latest prices of all trading pairs recently traded pairs modes supported by memory matching transactions matching of limit order and limit order matching market orders and limit orders matching limit orders with market orders matching market orders with market orders limit market order processing logic https hashcome cos 1251041754 cos ap hongkong myqcloud com githubimages limit 20market 20price 20trading png 2222 png note this picture is a long time ago the logic in the latest code is more complicated other features supported by match engine in addition to the ordinary matching functions of limit and market prices the matching trading engine of this system also introduces an active transaction mode by setting the trading start time initial issuance volume initial issuance price and activity of trading pairs such as btc usdt modes and other parameters can formulate a wealth of matching transaction modes to meet different matching modes for example the exchange is expected to launch the trading pair aaa usdt at 12 00 00 on august 8 2020 but as a newly launched currency how can it work without activity the project party or the exchange decided to come up with 10 000 aaa at a price of 0 0001usdt market price 0 0005 for everyone to snap up the system supports the setting of such activities in addition if the project party or the exchange decides to take out 10 000 aaas to issue at the price of 0 0001usdt i don t want everyone to snap up but hope that all users who recharge usdt can divide 10 000 aaas on average this system also supports the setting of this activity to sum up n short this system supports a highly customized matching mode at the same time you can also develop your own matching transaction mode just by modifying the matching logic in the exchange project about the technical composition backend development spring springmvc springdata springcloud springboot database mysql mongodb other redis kafka ali oss tencent captcha frontend vue iview less demo website https www bizzan com https www bizzan com this was done for the customer but later the customer stopped operating so this website was left because i don t have server permissions so this website may not be accessible at any time building a test site requires purchasing several cloud servers which cost a lot so i did not set up a test station myself but the system is complete and has passed the commercial and practical operation test for nearly a year about trading robots trading robots are automatic trading programs that can automatically trade based on external market conditions so that the exchange s trading pair prices are consistent with the external preventing losses caused by some users moving bricks system operating environment 1 centos 6 8 2 mysql 5 5 16 3 redis x64 3 2 100 4 mongodb 3 6 13 5 kafka 2 11 2 2 1 6 nginx 1 16 0 7 jre 8u241 8 jdk 1 8 9 vue 10 zookeeper recommended configuration for production environment https hashcome cos 1251041754 cos ap hongkong myqcloud com githubimages server 20configuration png qq 20200406204341 png file directory description 00 framework admin background management api bitrade job task management empty chat otc chat cloud springcloud eureka core core exchange match trading exchange api order api exchange core order core jar other lib market market api k line service otc api otc trade api otc core otc core sql sql script ucenter api user api wallet wallet 01 wallet rpc bitcoin bsv btm eos erc eusdt erc token erc20 eth ltc usdt 02 app android 03 app ios 04 web admin 05 web front use tutorial 1 prepare the mysql database and create a database named xxxx 2 prepare redis cache database 3 prepare kafka streaming environment first configure to run zookper then configure to run kafka 4 prepare mongodb database environment create users admin xxxx create bitrade database 5 prepare alibaba cloud oss modify the place to be configured in the project 6 prepare nginx and modify the configuration file optional need to be configured for official launch 7 modify the configuration file in the framework code to prepare the environment configuration parameters 8 compile to generate jar executable file 9 run cloud jar microservices registration center 10 run exchange jar match trading engine 11 run market jar quote center need to wait for exchange jar to fully start 12 run ucenter jar user center 13 run other modules wallet jar chat jar otc api jar etc 14 open mysql and import the xxxxxxx sql file in the sql folder in the framework code note that if the trigger sql reports an error you need to add a trigger for the wallet table 15 run the front end vue project 16 run the back end vue project 17 run wallet rpc 18 run the automated trading robot program the code in this part is not uploaded but it does not affect 19 run the admin project the service does not depend on other services so you can just run this project and directly view the background technical support this digital currency trading system is a project developed by my company for an exchange the exchange has ceased operations due to team reasons and our company was disbanded in february since i participated in the project i was responsible for overall r d management architecture design and customer docking so i mastered all the codes there are some places that need special attention in the use of the function of this system such as other operations after the new transaction pair improper operation will cause data disorder errors i can provide paid technical assistance and use training guidance email 877070886 qq com precautions when the memory is insufficient enter top in the linux console to view the java process occupies a lot of memory a java process occupies more than 1g because there are many jar packages to run so you need to control the memory used by certain jar packages you can choose a few less resource intensive projects are as follows java jar xms128m xmx128m xmn200m xss256k admin api jar java jar xms512m xmx512m xmn200m xss256k cloud jar java jar xms512m xmx512m xmn200m xss256k wallet jar about mail sms 1 this system supports the operation status of the system for sending emails and short messages 2 system notification alarm support user registration user authentication user recharge withdrawal currency rpc operation status system resource usage monitoring etc 24 kinds of monitoring questions about database scripts some reported that there is no complete sql file this is because the successfully compiled jar will automatically map the entity to a database structure after the first run the sql in the project only completes some database structures that springcloud cannot complete the automatic database configuration is located in the application properties configuration file jpa spring jpa show sql true spring data jpa repositories enabled true spring jpa hibernate ddl auto update spring jpa hibernate ddl auto update this configuration will automatically update the database structure core function description user side x 1 registration login real name authentication audit currently only supports mobile phones secondary development can be added to the mail very simple x 2 banner announcement help customized page banner supports separate settings for pc and app helps support various classification modes x 3 fiat currency c2c transaction fiat currency otc transaction supports two fiat currency models the platform can undertake c2c fiat currency exchange in the early stage of the project and otc transactions can be opened later x 4 coin trading support for limit order market order and other commission modes can be added for secondary development x 5 invite registered promotion partners support for ranking statistics on the number of invited promoters and commissions by day week and month x 6 innovation lab there are many supported functions in this part and itemized explanations in addition the app does not support this function for the time being x 6 1 first launch panic buying activity mode for example when issuing a new trading pair a certain number of currencies can be set on the trading pair for panic buying x 6 2 the first distribution mode of activity for example before issuing the btc usdt trading pair the official took out 5btc for the activity and divided the btc equally according to how much usdt the user recharged mortgaged x 6 3 panic buying mode for example before the zzz usdt trading pair is issued the zzz currency price is 5usdt and the official issuance activity price is 0 5usdt you can use this mode x 6 4 control panel sharing mode such as 6 3 only average distribution x 6 5 mining machine activity mode support users to mortgage a certain amount of currency and the official promise to return a certain amount of currency every month x 7 red envelope function support platform and official to issue a certain amount of currency red envelope this function is suitable for user fission x 8 various basic management such as user asset management flow management commission management real name management core function description management side x 1 summary view platform operating data including transaction amount registered number recharge etc x 2 member management member information management member real name verification member real name management member balance management member recharge freeze balance etc x 3 invitation management member invitation information member invitation ranking management x 4 ctc management ctc order management flow management acceptor management x 5 content management pc advertising management app advertising management announcement management help management x 6 financial management charge and withdrawal management financial flow management reconciliation management currency wallet balance management x 7 currency management new trading pair management trading pair new trading robot setting trading robot parameters setting market engine trading engine revoking all orders x 8 event management new activity mining machine subscription panic buying division management x 9 red envelope management platform red envelope management user red envelope management x 10 system management role management department management user management authority management currency management rpc management version management x 11 margin management this function is considered in design but not used during actual operation x 12 otc management advertising management order management otc currency management surrender management etc this function has not been verified by actual operation about blockchain wallet rpc this project provides two wallet docking methods one is self built node blockchain browser and the other is third party wallet docking if you want to use a self built node or blockchain browser you can directly compile the code in 00 framework if you want to use a third party wallet for docking you can download the project files of the youdun wallet in the 07 uduncloud folder and copy them to 00 framework after you get the code you can not connect the blockchain nodes during the debugging and running of this project which will not have much impact even if you do not connect the blockchain nodes you can deploy one of them with matching transaction function trading platform just that users cannot recharge their wallet addresses when you are gradually familiar with the entire system and have a certain basic reserve of blockchain operation principles node construction and blockchain browser you can start to study the projects under the 01 wallet rpc folder each currency corresponds to different data access methods most blockchain projects have the same or very similar wallet operation methods for example bitcoin derivatives such as btc ltc bch bsv bcd etc have almost the same api operations the same another example is eth when you master the operation of a contract currency the operation of other digital currencies based on eth is almost the same so basically when you spend time understanding one you understand a bunch of currencies the wallet operation scheme used in this project is also different and as far as possible to show you different usages self built full nodes such as btc and usdt now require almost 300g of hard disk space like eth self built light nodes are used reference article https www cnblogs com bizzan p 11341713 html because the full node requires too much hard disk space such as bch bsv etc use a third party blockchain browser to obtain data like xrp the official has provided an interface to access block data ripple api github address https github com ripple ripple lib generally speaking when the amount of funds exchanged by the exchange is not large you can explore it yourself but when the amount of funds exchanged is large if you are not confident about operating your wallet you can also use a third party wallet service of course this requires you to negotiate with the wallet service provider to pay an annual fee or something the following figure is a brief explanatory diagram of the user recharge monitoring logic just take a look at it https images gitee com uploads images 2020 0327 162223 5d418523 2182501 png 13981024 76374161aedf70d6 png system display pc front end https images gitee com uploads images 2020 0327 135803 75ec9a0b 2182501 png 01 png https images gitee com uploads images 2020 0327 135834 4a5fb1c4 2182501 png 02 png https images gitee com uploads images 2020 0327 135902 a7286b9c 2182501 png 03 ctc png https images gitee com uploads images 2020 0322 193759 edc5dc7b 2182501 png 5 png https images gitee com uploads images 2020 0327 135930 0c02d004 2182501 png 04 png https images gitee com uploads images 2020 0327 140037 074a81a4 2182501 png png https images gitee com uploads images 2020 0327 140003 9b962fe7 2182501 png 07 png https images gitee com uploads images 2020 0322 193852 3ad12a6f 2182501 png 8 png https images gitee com uploads images 2020 0322 193902 ef09925e 2182501 png 9 png system operation display app front end https images gitee com uploads images 2020 0322 193927 9940ca7c 2182501 jpeg 10 jpg https images gitee com uploads images 2020 0322 193941 ff5a16a2 2182501 jpeg 11 jpg k https images gitee com uploads images 2020 0322 193951 abf7b5b6 2182501 jpeg 12 jpg https images gitee com uploads images 2020 0322 194003 d14a772a 2182501 jpeg 13 jpg https images gitee com uploads images 2020 0322 194021 a047d3a5 2182501 jpeg 14 jpg https images gitee com uploads images 2020 0322 194059 faeeeb4a 2182501 jpeg 15 jpg https images gitee com uploads images 2020 0322 194112 7ae11b00 2182501 jpeg 16 jpg some pages on the mobile phone web app https images gitee com uploads images 2020 0325 130921 7d8dee06 2182501 jpeg 12 jpg https images gitee com uploads images 2020 0325 130936 18809c8f 2182501 jpeg 11 jpg https images gitee com uploads images 2020 0325 130948 e36b562d 2182501 jpeg 13 jpg system operation display back end https images gitee com uploads images 2020 0322 194251 9b5293ff 2182501 png 17 png https images gitee com uploads images 2020 0322 194305 f83e4f90 2182501 png 18 png https images gitee com uploads images 2020 0322 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download3 png https images gitee com uploads images 2020 0324 182850 8b19fe57 2182501 png download4 png https images gitee com uploads images 2020 0324 182856 9206a79a 2182501 png download5 png attention anyone who uses this source code to engage in commercial activities and causes losses to others and himself is not responsible for me | cryptocurrency-exchanges coinexchange otc cryptocurrency | front_end |
apps | polkadot apps a portal into the polkadot and substrate networks provides a view and interaction layer from a browser this can be accessed as a hosted application via https polkadot js org apps or you can access the ipfs hosted version via https polkadot js org apps ipfs via hash or https dotapps io via ipns to explore any of the supported polkadot and substrate chains if you run one or more ipfs node s pinning the ui which only gets updated on releases will make it faster for you and others you can find details about that below in the ipfs chapter below important if you are a chain developer and would like to add support for your chain to the ui all the local configuration api types settings logos can be customized in the apps config package packages apps config readme md complete with instructions of what goes where overview the repo is split into a number of packages each representing an application development contributions are welcome to start off this repo along with others in the polkadot https github com polkadot js family uses yarn workspaces to organize the code as such after cloning dependencies should be installed via yarn not via npm the latter will result in broken dependencies to get started 1 clone the repo locally via git clone https github com polkadot js apps optional local path 2 ensure that you have a recent lts version of node js for development purposes node 16 https nodejs org en is recommended 3 ensure that you have a recent version of yarn for development purposes yarn 1 22 https yarnpkg com docs install is required 4 install the dependencies by running yarn 5 ready now you can launch the ui assuming you have a local polkadot node running via yarn run start 6 access the ui via http localhost 3000 http localhost 3000 docker you can run a docker container via docker run rm it name polkadot ui e ws url ws someip 9944 p 80 80 jacogr polkadot js apps latest to build a docker container containing local changes docker build t jacogr polkadot js apps f docker dockerfile when using these docker commands you can access the ui via http localhost 80 or just http localhost ipfs ipfs allows sharing files in a decentralized manner in a similar fashion the polkadot network exchanges blocks ipfs works best when many nodes seed the same data nodes can seed specific data by pinning them you can pin with the following command curl s https polkadot js org apps ipfs pin json jq jr ipfshash xargs 0 i cid ipfs pin add progress cid here is a script you can save as usr local bin polkadotjs ipfs pin sh usr bin env bash ipfs usr local bin ipfs curl s https polkadot js org apps ipfs pin json jq jr ipfshash xargs 0 i cid ipfs pin add progress cid i suggest to run the script once the output should be similar to the cid hash will very likely be different though usr local bin polkadotjs ipfs pin sh pinned qmnyabzae8kraf68yin3zuuxgdwroeav3jhicshsg5b2ow recursively now that you know the cid hash you can check whether the data is already pinned or not ipfs pin ls grep qmnyabzae8kraf68yin3zuuxgdwroeav3jhicshsg5b2ow qmnyabzae8kraf68yin3zuuxgdwroeav3jhicshsg5b2ow recursive now that we know it works we can automate that with a cron task run crontab e if you see only comments append the following to the file and save shell bin bash home 0 usr local bin polkadotjs ipfs pin sh dev null 2 1 now our script will run every hours at minute 0 8 00 9 00 etc to check we can unpin temporarily ipfs pin rm qmnyabzae8kraf68yin3zuuxgdwroeav3jhicshsg5b2ow unpinned qmnyabzae8kraf68yin3zuuxgdwroeav3jhicshsg5b2ow now asking for the cid confirms that is it not there ipfs pin ls qmnyabzae8kraf68yin3zuuxgdwroeav3jhicshsg5b2ow error path qmnyabzae8kraf68yin3zuuxgdwroeav3jhicshsg5b2ow is not pinned wait until the your cron task runs and try again ipfs pin ls qmnyabzae8kraf68yin3zuuxgdwroeav3jhicshsg5b2ow qmnyabzae8kraf68yin3zuuxgdwroeav3jhicshsg5b2ow recursive tada this is now automatic and you may forget it if you are curious and want to know how many people seed the ui on ipfs here is the magic command it may take a while to return the answer as ipfs will search for about 1 minute ipfs dht findprovs qmtejwb7mjpbhboqubjzhsgsxflmcjnza3lfefqoqc87vj wc l if you are current about the content of what you just pinned you may use the following command ipfs ls qmtejwb7mjpbhboqubjzhsgsxflmcjnza3lfefqoqc87vj qmpjgyqvccxm238noz7tzdbyyga35qqc8g6sfyxf3kdxz3 38078 favicon ico qmdouvsve9rmvb84cy1ehvi1lagw1fkcqqqxsejgxjrv7h 668 index html qmwhcgf1jcfzcyjzsw52vm5rijvbcnpx1fo2nyobkbvtuf ipfs qmt6nwdsjzmybs6bmq845nmumejwbixbfnxa9hdahamdsg locales qmcgizpwvpt1e1dkss3zr5je89rzrvocnkpebgwhn3jvtc 2178582 main ce05dfca js qmdnetuhfdyw5tjr82bfpzyvefrbkyjjanuvbvzwt18ygg 337 manifest json qmw7gdkhbmtd7srtqsvyo84bdpyypzr3w1wqo8pme2q5hc next qmd8unrqibobm4qb6dhic1hoq7svwzrwjenon3jpev3iif 480594 polkadotjs 3af757ad js qmufxpmfnys8y8dekuankbx7bhisajalcpbdkh6f5ddcnm 628284 react 0cecb00d css qmsegxdqbc1ek9td1mhy3brvjpfwhm9zqyegtgauj1qc4g 924156 react 8f083b49 js qmfgbgfe2aqf83wv21m9k5dh2ew89cdj4tydoxjwdk6nnl 1552 runtime 3d77e510 js qmypa8jchh7gfopmalr5xtw4i1qm2xgvbe3nep11y3tera static qmeybc5egbccc8newxc2rvbd93yihttm5xyzqcdohxerdf 859984 vendor 8b793a81 js desktop app the main advantage of using desktop app is that it by default stores encrypted accounts on the filesystem instead of browser s local storage local storage is susceptible to attacks using xss cross site scripting there s no such risk when with files stored on disk the desktop app uses the electron https www electronjs org framework it provides the same features as web app the only difference being different account storage the accounts are stored in the following directories mac library application support polkadot apps polkadot accounts linux config polkadot apps polkadot accounts or xdg config home polkadot apps polkadot accounts if xdg config home is defined windows appdata polkadot apps polkadot accounts for more details on the desktop app head over to electron package readme https github com polkadot js apps blob master packages apps electron readme md | polkadot substrate polkadot-js ui blockchain wallet | blockchain |
P9-front-end-dashboard | project 9 front end dashboard this repo contains all the source code to run the micro api for the sports analytics dashboard sportsee 1 general information to start this project you are free to use docker or not in this documentation we will see several methods to launch the project easily 2 project without docker 2 1 prerequisites nodejs version 12 18 https nodejs org en yarn https yarnpkg com if you are working with several versions of nodejs we recommend you install nvm https github com nvm sh nvm this tool will allow you to easily manage your nodejs versions 2 2 launching the project fork the repository clone it on your computer the yarn command will allow you to install the dependencies the yarn dev command will allow you to run the micro api 3 project with docker 2 1 prerequisites docker desktop https www docker com products docker desktop 2 2 starting the project the docker image build no cache t micro api command will allow you to build your image the docker container run name micro api p 3000 3000 dt micro api yarn command will allow you to create your docker container and run your image on port 3000 the docker container stop micro api command will allow you to stop your micro api the docker container rm micro api command will allow you to delete your micro api container 2 3 vscode and container remotes finally if you have vscode you can easily launch your project in a docker environment you will need the remote development extension https marketplace visualstudio com items itemname ms vscode remote vscode remote extensionpack once you have this extension installed just click on the reopen in container button once in the container run the yarn dev command 4 endpoints 4 1 possible endpoints this project includes four endpoints that you will be able to use http localhost 3000 user userid retrieves information from a user this first endpoint includes the user id user information first name last name and age the current day s score todayscore and key data calorie macronutrient etc http localhost 3000 user userid activity retrieves a user s activity day by day with kilograms and calories http localhost 3000 user userid average sessions retrieves the average sessions of a user per day the week starts on monday http localhost 3000 user userid performance retrieves a user s performance energy endurance etc warning currently only two users have been mocked they have userid 12 and 18 respectively 4 2 examples of queries http localhost 3000 user 12 performance retrieves the performance of the user with id 12 http localhost 3000 user 18 retrieves user 18 s main information | front_end |
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gsm8k-ScRel | scaling relationship on learning mathematical reasoning with large language models the code and data used for reproducing results of scaling relationship on learning mathematical reasoning with large language models https arxiv org abs 2308 01825 and query and response augmentation cannot help out of domain math reasoning generalization https arxiv org abs 2310 05506 2023 10 we have a new paper that investigates the scaling of in domain and out of domain generalization on augmented math problems 2023 9 paper updated with more details on 65b and 70b models setting 7b 7b 2 13b 13b 2 33b 65b 70b 2 icl 8shot 11 0 18 1 14 6 17 8 29 3 28 7 35 6 53 1 50 9 69 7 56 8 sft 35 9 48 7 41 6 55 4 43 0 55 2 50 0 61 7 54 6 59 3 63 2 rft k 100 41 7 52 7 47 5 58 7 49 1 59 9 54 8 65 4 54 5 rft u13b 49 3 61 8 50 3 65 6 52 1 66 2 55 4 69 1 56 5 59 0 62 3 rft u33b 49 1 61 6 51 2 64 1 51 4 66 3 55 3 69 1 57 9 59 7 64 8 metrics are maj1 1 and maj1 100 findings from the paper fig1 fig model performance png fig2 fig head png sft training if you cannot reproduce our results please try using transformers 4 29 and test with batch size 1 use train xb sh for fine tuning llama and llama 2 bash bash train xb sh data train use jsonl save path 3 rft inference llama 7b 13b bash bash group sample 7b 13b sh save path llama 30b bash bash group sample 30b sh save path filter reasoning paths python python collect rejection sampling py rft training for rft using llama 7b 7b 2 13b 13b 2 33b generated samples with k 100 bash bash train xb sh data rft llama yb jsonl save path 3 for rft using u13b bash bash train xb sh data rft u13b jsonl save path 3 for rft using u33b bash bash train xb sh data rft u33b jsonl save path 3 evaluation we use greedy decode for the test set for evaluate 7b 13b models bash bash test 7b 13b sh save path for evaluate 30b models bash bash single test 30b sh save path 0 data test jsonl sh for evaluate 65b 70b models bash bash single test 65b sh save path 0 1 data test jsonl sh use eval py to obtain the scores and it also supports maj1 k gpu usage 7b 13b 33b 65b 70b sft rft 8 16 32 minimal inference 1 1 2 group inference 8 8 8 checkpoints 7b 7b2 13b 13b2 33b rft k 100 ofa sys gsm8k rft llama7b sample100 https huggingface co ofa sys gsm8k rft llama7b sample100 rft u13b ofa sys gsm8k rft llama7b u13b https huggingface co ofa sys gsm8k rft llama7b u13b ofa sys gsm8k rft llama7b2 u13b https huggingface co ofa sys gsm8k rft llama7b2 u13b ofa sys gsm8k rft llama13b u13b https huggingface co ofa sys gsm8k rft llama13b u13b ofa sys gsm8k rft llama13b2 u13b https huggingface co ofa sys gsm8k rft llama13b2 u13b rft u33b ofa sys gsm8k rft llama33b u33b https huggingface co ofa sys gsm8k rft llama13b u13b citation misc yuan2023scaling title scaling relationship on learning mathematical reasoning with large language models author zheng yuan and hongyi yuan and chengpeng li and guanting dong and keming lu and chuanqi tan and chang zhou and jingren zhou year 2023 eprint 2308 01825 archiveprefix arxiv primaryclass cs cl misc li2023query title query and response augmentation cannot help out of domain math reasoning generalization author chengpeng li and zheng yuan and guanting dong and keming lu and jiancan wu and chuanqi tan and xiang wang and chang zhou year 2023 eprint 2310 05506 archiveprefix arxiv primaryclass cs cl | ai |
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ark | h1 align center ark h1 p align center img alt codecov src https img shields io codecov c gh chakra ui ark style for the badge token o6bb59dhj4 img alt npm src https img shields io npm l ark ui react style for the badge img alt github stars src https img shields io github stars chakra ui ark logo github style for the badge p available components react solid vue accordion avatar carousel checkbox color picker date picker dialog combobox autocomplete editable environment file upload hover card menu number input pagination pin input popover pressable radio group rating select segment group slider splitter switch tabs tags input toast togglegroup tooltip | headless react vue solid color-picker accordion carousel checkbox combobox dialog editable menu pagination popover select tabs toast | os |
oncall | oncall gitter chat https badges gitter im irisoncall lobby png https gitter im irisoncall lobby build status https circleci com gh linkedin oncall svg style shield https circleci com gh linkedin oncall p align center img src https github com linkedin oncall raw master docs source static demo png width 600 p see admin docs http oncall tools docs admin guide html for information on how to run and manage oncall development setup local machine details summary see instructions for setting up oncall on your local machine summary prerequisites debian ubuntu sudo apt get install libsasl2 dev python3 dev libldap2 dev libssl dev python pip python setuptools mysql server mysql client install bash python setup py develop pip install e dev setup mysql schema bash mysql u root p db schema v0 sql setup app config by editing configs config yaml optionally you can import dummy data for testing bash mysql u root p o oncall db dummy data sql run one of the following commands goreman start procman start make serve oncall dev configs config yaml test bash make test details docker compose details summary see instructions for using code docker compose code summary running bash make compose or running docker compose directly bash docker compose up build limitations doesn t currently provide a mechanism for running tests requires rebuilding to apply code changes doesn t tail python logs to stdout details contributing check out https github com linkedin oncall issues for a list of outstanding issues and tackle any one that catches your interest contributions are expected to be tested thoroughly and submitted with unit end to end tests look in the e2e directory for our suite of end to end tests | oncall calendar scheduling | os |
drf-angular-docker-tutorial | drf angular docker tutorial dockerized django back end api with angular front end tutorial follow the tutorial series here to understand how it all works django api with angular app in docker tutorial https dragonprogrammer com dockerized django api angular tutorial technologies used django 2 1 5 django rest framework 3 9 0 angular 7 2 docker engine 18 09 0 1 building a basic api with django rest framework in docker https dragonprogrammer com dockerized django api angular tutorial 2 adding detail views to a django drf api in docker https dragonprogrammer com adding detail views django drf api 3 building an angular app in a secure and compact docker image https dragonprogrammer com building angular docker 4 connecting an angular app to a rest api https dragonprogrammer com connecting angular api 5 improving an angular todo app to manage tasks via a rest api https dragonprogrammer com angular app manage tasks api 6 securing a django rest framework api using auth0 https dragonprogrammer com securing django api auth0 7 securing an angular app using auth0 and jwt authentication https dragonprogrammer com securing angular auth0 8 adding object level permissions in django rest framework https dragonprogrammer com object level permissions drf 9 preparing a django drf api for production in docker https dragonprogrammer com django drf api production docker 10 preparing an angular app for production in docker https dragonprogrammer com angular app production docker 11 building a docker image in google cloud build https dragonprogrammer com building docker image google cloud build 12 building a docker image from a private github or bitbucket repository in google cloud build https dragonprogrammer com docker image private repo cloud build 13 connecting django to a postgresql database in cloud sql https dragonprogrammer com connect django database cloud sql 14 deploying a docker container on a vm in google cloud platform https dragonprogrammer com deploy docker container gcp 15 serving an angular app s static files from google cloud storage https dragonprogrammer com serve angular files cloud storage | docker django django-rest-framework drf angular api rest-api dockerized python auth0 google-cloud-platform gcp jwt-authentication | front_end |
PyML | python 01 2021 11 01 2021 11 05 02 2021 12 13 2021 12 17 03 2022 01 17 2022 01 21 04 2022 02 21 2022 02 25 05 2022 03 28 2022 04 01 06 2022 04 25 2022 04 29 07 2022 05 23 2022 05 27 08 2022 07 25 2022 07 29 10 2022 10 17 2022 10 21 11 2022 11 21 2022 11 25 12 2022 12 26 2022 12 30 | machine-learning python course | ai |
docker-laravel | laravel to docker laravel tags 4 2 4 2 11 4 2 dockerfile 4 2 dockerfile 5 0 5 0 16 5 0 dockerfile 5 0 dockerfile 5 1 5 1 4 5 1 dockerfile 5 1 dockerfile note these containers using php 5 6 apache what is laravel laravel is a free open source php web application framework created by taylor otwell and intended for the development of web applications following the model view controller mvc architectural pattern prominent laravel features include its expressive syntax a modular packaging system with a dedicated dependency manager different ways for accessing relational databases and various utilities that aid in application deployment and maintenance wikipedia org wiki laravel https wikipedia org wiki laravel laravel logo https upload wikimedia org wikipedia commons thumb 3 3d laravellogo png 250px laravellogo png docker pull command bash docker pull alfa30 laravel especific version 5 1 docker pull alfa30 laravel 5 1 5 0 docker pull alfa30 laravel 5 0 4 2 docker pull alfa30 laravel 4 2 build laravel 5 1 bash docker build t alfa30 laravel 5 1 5 1 develop terminal bash docker run rm it p 8900 80 alfa30 laravel 5 1 bash docker run rm it p 8900 80 alfa30 laravel 5 1 build laravel 5 bash docker build t alfa30 laravel 5 0 5 0 develop terminal bash docker run rm it p 8900 80 alfa30 laravel 5 0 bash docker run rm it p 8900 80 alfa30 laravel 5 0 build laravel 4 2 bash docker build t alfa30 laravel 4 2 4 2 develop terminal bash docker run rm it p 8900 80 alfa30 laravel 4 2 bash docker run rm it p 8900 80 alfa30 laravel 4 2 | front_end |
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ITIS | itis information technology infrastructure service itil itil it itis it it itis it curl lo minikube http kubernetes oss cn hangzhou aliyuncs com minikube releases v0 28 1 minikube darwin amd64 chmod x minikube sudo mv minikube usr local bin | server |
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blk-design-system-react | blk design system react https demos creative tim com blk design system react tweet https img shields io twitter url http shields io svg style social logo twitter https twitter com home status material 20kit 20pro 20is 20a 20bootstrap 20ui 20kit 20with 20a 20fresh 20new 20design 20inspired 20by 20google s 20material 20design 20 e2 9d a4 ef b8 8fhttps 3a demos creative tim com material kit pro presentation html 20 23bootstrap 20 23material 20 23design 20 23uikit 20 23premium 20 20via 20 40creativetim version https img shields io badge version 1 2 2 blue svg license https img shields io badge license mit blue svg github issues open https img shields io github issues creativetimofficial blk design system react svg maxage 2592000 https github com creativetimofficial blk design system react issues q is 3aopen is 3aissue github issues closed https img shields io github issues closed raw creativetimofficial blk design system react svg maxage 2592000 https github com creativetimofficial blk design system react issues q is 3aissue is 3aclosed join the chat at https gitter im nit dgp general https badges gitter im nit dgp general svg https gitter im creative tim general lobby chat https img shields io badge chat on 20discord 7289da svg https discord gg e4ahaqy product presentation image https github com creativetimofficial public assets blob main blk design system react blk design system react jpg raw true blk design system react http demos creative tim com blk design system react is a responsive bootstrap 4 kit developed using react https reactjs org reactstrap https reactstrap github io and create react app https facebook github io create react app and it is provided for free by creative tim it is a beautiful cross platform ui kit featuring over 70 elements and 3 templates blk design system react will help you create a clean and simple website that is a perfect fit for today s black design it is built using the 12 column grid system with components designed to fit together perfectly it makes use of bold colours beautiful typography clear photography and spacious arrangements complex documentation each element is well presented in a very complex documentation you can read more about the idea behind this design system here you can check the components here and the foundation here bootstrap 4 support blk design system react is built on top of the much awaited bootstrap 4 reactstrap this makes starting a new project very simple it also provides benefits if you are already working on a bootstrap 4 or reactstrap project you can just import the blk design system react style over it most of the elements have been redesigned but if you are using an element we have not touched it will fall back to the bootstrap default table of contents versions versions pro versions pro versions demo demo quick start quick start documentation documentation file structure file structure browser support browser support resources resources reporting issues reporting issues licensing licensing useful links useful links versions img src https github com creativetimofficial public assets blob main logos html logo jpg raw true width 60 height 60 https www creative tim com product blk design system ref blkdsr readme img src https github com creativetimofficial public assets blob main logos react logo jpg raw true width 60 height 60 https www creative tim com product blk design system react ref blkdsr readme img src https github com creativetimofficial public assets blob main logos angular logo jpg raw true width 60 height 60 https www creative tim com product blk design system angular ref blkdsr readme html react angular blk design system html https github com creativetimofficial public assets blob main blk design system opt blk thumbnail jpg raw true https www creative tim com product blk design system blk design system react https raw githubusercontent com creativetimofficial public assets main blk design system react blk design system react jpg https www creative tim com product blk design system react blk design system angular https raw githubusercontent com creativetimofficial public assets main blk design system angular opt blk angular thumbnail jpg https www creative tim com product blk design system angular pro versions img src https github com creativetimofficial public assets blob main logos html logo jpg raw true width 60 height 60 https www creative tim com product blk design system pro ref blkdsr readme img src https github com creativetimofficial public assets blob main logos react logo jpg raw true width 60 height 60 https www creative tim com product blk design system pro react ref blkdsr readme img src https github com creativetimofficial public assets blob main logos angular logo jpg raw true width 60 height 60 https www creative tim com product blk design system pro angular ref blkdsr readme html react angular blk design system pro html https github com creativetimofficial public assets blob main blk 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bower io bower install blk design system react clone the repo git clone https github com creativetimofficial blk design system react git documentation the documentation for the blk design system react is hosted at our website https demos creative tim com blk design system react documentation overview file structure within the download you ll find the following directories and files blk design system react changelog md issue template md readme md package json public favicon ico index html manifest json src index js variables charts js assets css blk design system react css blk design system react css map blk design system react min css nucleo icons css demo demo css fonts nucleo eot nucleo ttf nucleo woff nucleo woff2 img scss blk design system react bootstrap mixins utilities custom cards mixins sections utilities vendor react react differences scss blk design system react scss components footer footer js navbars componentsnavbar js examplesnavbar js pageheader pageheader js views 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creativetimofficial public assets main black dashboard pro django opt bdp django thumbnail jpg https www creative tim com product black dashboard pro django reporting issues we use github issues as the official bug tracker for the blk design system here are some advices for our users that want to report an issue 1 make sure that you are using the latest version of the blk design system check the changelog from your dashboard on our website https www creative tim com ref blkdsr readme 2 providing us reproducible steps for the issue will shorten the time it takes for it to be fixed 3 some issues may be browser specific so specifying in what browser you encountered the issue might help licensing copyright 2023 creative tim https www creative tim com ref blkdsr readme licensed under mit https github com creativetimofficial blk design system react blob main license md useful links tutorials https www youtube com channel ucvytg4scw rovb9ohkzzd1w affiliate program https www creative tim com 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modern-embedded-programming-course | brought to you by quantum leaps https www state machine com attachments logo ql 400 png https www state machine com p align center a href https www youtube com statemachinecom target blank title quantumleaps on youtube img src img yt masthead jpg a p modern embedded systems programming course welcome to the modern embedded systems programming video course https www youtube com playlist list plpw8o6w 1chwytzi3bhwblbgqopfxpapm in this course you ll learn how to program embedded microcontrollers the modern way from the basics all the way to the contemporary modern embedded programming practice the unique approach of this course is to step down to the machine level frequently and show you exactly what happens inside your embedded microcontroller this deeper understanding will allow you to apply the concepts more efficiently and with greater confidence if you are looking for a practical hands on well structured and in depth course explaining the essential concepts in embedded programming this free course is right for you relevance the course started already in 2013 so a legitimate quesion is is it still relevant the answer is yes perhaps even more so than in 2013 for two main reasons fundamental concepts this course focuses on the essential and fundamental concepts in embedded programming which never go out of style all presetned concepts are covered in depth and include binary representations two s complement hexadecimal notation flow of control status register branch instructions variables arrays and pointers interfacing with the outside world gpio bitwise operations in c functions call stack recursion arm procedure call standard standard integers stdint h and mixing integer types structures in c and cmsis startup code vector table embedded software build process linking process interrupts and race conditions superloop architecture rtos real time operating systems object oriented programming including oop in c event driven programming active objects state machines including modern hierarchical state machines automatic code generation software tracing assertions and design by contract arm cortex m architecture this course focuses on the prevalent b arm cortex m b https www state machine com course arm cortex m for beginners pdf architecture which over the past decade became unquesionably dominat in the embedded mcu market familiarity with arm cortex m is the most sought after skill that employers are looking for p align center a href https www state machine com course arm cortex m for beginners pdf target blank title read arm cortex m for beginners img src img arm processors png a br em arm processors including the cortex m family em p instructor the course is designed and taught by b miro samek b https www state machine com interview with miro samek an embedded software expert with over 30 years of experience miro enjoys teaching and this video course https www youtube com playlist list plpw8o6w 1chwytzi3bhwblbgqopfxpapm his books https www state machine com category books articles https www state machine com an articles and conference talks https embeddedonlineconference com speaker miro samek helped many developers improve their skills pass tough job interviews and get hired for embedded programming positions p align center a href https www state machine com interview with miro samek target blank title read interview with miro samek img src img miro jpg a br em miro samek em p prerequisites the course starts with the basics but this part is short and focused on the embedded aspects of programming in c therefore you might need to supplement this course with a general study of the c programming language you might also want to learn a bit about how a cpu works also this course is hands on meaning that to get the most out of this course you can and should follow along and run the discussed projects on your pc to do this you will need some hardware hardware an embedded board and software software an embedded development toolset note br several early lessons use a simulator and therefore you don t need the embedded board right away more advanced lessons where you interact with the mcu peripherals such as gpio etc require an embedded board hardware the main embedded board used throughout the course is the tivac launchpad https www ti com tool ek tm4c123gxl board a k a ek tm4c123gxl based on the arm cortex m4f microcontroller from texas instruments the board is inexpensive and is still available for purchase from multiple electronic distributors it is self contained and provides a built in hardware debugger programmer stellaris icdi that enables single step debugging and inspecting the internal state p align center a href https www ti com tool ek tm4c123gxl target blank title tivac launchpad ek tm4c123gxl img src img ek tm4c123gxl jpg a br em tivac launchpad ek tm4c123gxl em p the course downloads projects for the course now also contain project versions for the stm32 nucleo c031c6 based on the arm cortex m0 mcu the board is also inexpensive self contained and includes an even more versatile built in hardware debugger st link that enables single step debugging and inspecting the internal state p align center a href https www st com en evaluation tools nucleo c031c6 html target blank title stm32 nucleo c031c6 img src img stm32 nucleo c031c6 jpg a br em stm32 nucleo c031c6 em p note br course projects for other inexpensive embedded boards will be added in the future software in order to build and run the code presented in this course you will need one of the following embedded toolsets iar ewarm the course started with the iar embedded workbench for arm ewarm https www iar com which is used in lessons 1 19 iar ewarm is a professional toolset with a good compiler and stable debugger p align center a href https www iar com target blank title iar systems img src img iar ewarm png a br em iar ewarm with one of the projecs em p note br iar ewarm used to be available under a free size limited kickstart licensing but recently iar systems stopped offering free licenses the only free option left is a 2 week evaluation license projects for iar ewarm have been updated to the newer versions of the toolset and are provided for lessons 1 19 keil mdk keil mdk https www keil com microcontroller development kit is another professional development toolset used in this video course in contrast to iar ewar keil mdk is offered under increasingly permissive licensing including free keil mdk v6 community edition https www keil arm com p align center a href https www keil com target blank title arm keil img src img keil mdk png a br em keil uvision ide with one of the projecs em p note br keil mdk projects are now available for all lessons of this course this includes lessons 1 21 which originally were presented for iar ewarm or ti ccs ti ccs due to popular demand two lessons of the course 19 and 20 demonstrate the code composer studio ccs https www ti com tool ccstudio ide from texas instruments the only valuable aspect here is the use of the open source gnu arm compiler and linker note br code composer studio ccs 11 uses the ti compiler by default and no longer comes with the gnu arm compiler installed but the gnu arm toolchain can be installed via the menu help install gcc arm compiler tools p align center a href https www ti com tool ccstudio target blank title code composer studio img src img ti ccs png a br em eclipse based code composer studio ide with one of the projecs em p the ccs ide is based on eclipse and for that reason it is painfully slow to launch and use the eclipse projects are threrefore difficult to share because they consist of multiple files and directories also projects cannot be simply opened in the ide but instead need to be imported the generated error messages are often confusing finally debugging is slow and unstable projects for the course this repository provides the project downloads that you can open in a specific embedded toolset and run on your pc at home the projects are organized as illustrated in the following annotated directory tree modern embedded programming course lesson 01 lesson number simulator iar simulator with iar ewarm workspace eww iar workspace simulator keil simulator with keil mdk rte run time environment for keil mdk lesson uvprojx uvision project lesson lesson 04 stm32c031 keil stm32c031 board with keil mdk rte run time environment for keil mdk tm4c123 iar tm4c123 board with iar ewarm workspace eww iar workspace tm4c123 keil tm4c123 board with keil mdk rte run time environment for keil mdk lesson uvprojx uvision project lesson lesson 19 tm4c123 ccs tm4c123 board with ccs ek tm4c123gxl board specific code targetconfigs ccs project directory ccsproject ccs project file csproject eclispe project file project eclipse project file updates all projects for arm keil uvision have been updated from the obsolete compiler 5 to the newer compiler 6 comments discussion if you would like to discuss this course or related subjects please post your questions or comments on youtube in the commend section under each pertaining video lesson other course resources numerous resources for the video course are available through the companion webpage at www state machine com video course https www state machine com video course among others you can find there information about the hardware board logic analyzer etc troubleshooting tivac launchpad https www state machine com course an troubleshooting tivac pdf tiva tm4c123gh6pm data sheet https www state machine com course tm4c123gh6pm datasheet pdf usb drivers for tivac https www state machine com course mdk stellaris icdi addon exe flash programmer for tivac https www ti com tool lmflashprogrammer and more how to help this project if you like this project please b subscribe to the quantum leaps youtube channel b https www youtube com channel ucmgxfeew8i6gzjg3twen4gw sub confirmation 1 p align center a href https www youtube com channel ucmgxfeew8i6gzjg3twen4gw sub confirmation 1 target blank title quantumleaps on youtube img src img yt subscribe png p a p spread the word about the videos you like e g by posting on other websites frequented by embedded folks give this github repository a star in the upper right corner of your browser window p align center img src img github star jpg p | learning-programming embedded-systems embedded c embedded-c rtos arm arm-cortex-m arm-cortex-m4f samek video-course learning learning-by-doing learning-labs architecture c-programming debugging interrutps low-level-programming | os |
everest | everest div class wikidoc p in short the everest framework is designed to ease the creation formatting and transmission of hl7v3 structures with remote systems nbsp p p the quot framework quot provides a series of consistent well documented components that when used together provide a flexible mechanism for supporting hl7v3 standards within application through a combination of automatically generated code and carefully constructed handwritten modules everest has the ability a to a serialize validate and transmit structures everest comes bundled with basic serialization capabilities for p ul li hl7 clinical document architecture r2 li li hl7v3 messaging li li normative edition 2008 li li normative edition 2010 li li pan canadian messaging specifications li li r02 04 01 li li r02 04 02 li li r02 04 03 li ul p br the serialization assemblies bundled with everest represent the structures contained within the mif files bundled with documentation where license permits functionality validation casting etc and structure meta data additional standards or documentation for the bundled dlls can be generated by processing model interchange format mif files version 2 1 2 2 1 3 2 1 4 2 1 5 and 2 1 6 using either the gpmr or gpmr wizard tools bundled with the framework the following additional standards are known to work with everest but are not included p ul li pan canadian cerx 4 3 messaging li li universal normative edition 2009 li ul p br everest currently supports serializing structures to from the following formats p ul li xml its 1 0 li li hl7v3 xml data types r1 uv and ca extensions li li hl7v3 xml data types r2 li li binary format li ul p br everest currently supports transporting structures to from other systems using the following connectors p ul li windows communication foundation server client mode basichttpbinding wshttpbinding ws2007httpbinding nettcpbinding li li file systems server client li li msmq publish only li ul p br the pillars of everest are p ul li strong intuitiveness strong all components within everest are designed to be intuitive to developers great care has been taken to reduce the complexity of the framework and allow developers to focus on hl7v3 messaging li li strong standards compliance strong being a standards based framework one of the foundational pieces is standards compliance the everest framework is more than just a serialization engine it will generate messages transport them and validate instances in a standards compliant manner li li strong quality strong everest code is held to the highest standard of quality in terms of regression testing and documentation all changes made to the framework are reviewed for their quality and are subject to over 8 000 tests li li strong performance strong everest has been designed with long term performance in mind many of the methods within everest especially formatting have the ability to quot learn quot and become faster the more they are used li li strong flexibility strong everest has been designed to be flexible in the manner that allows it to support new hl7v3 standards li ul h6 architecture h6 p the marc hi everest framework is modeled using a very loosely coupled architecture this design allows application developers to program against one set of hl7v3 models and serialize de serialize to many different implementable technology specification its formats the marc hi everest framework also allows applications to consume or produce these models using a wide array of transport mechanisms p p this flexible architecture ensures that the internal canonical data of your application is safely insulated from changes in the hl7v3 its or transport specifications p p img src http te marc hi ca projects ev images framework diagram jpg alt framework diagram p h2 continuous integration status h2 p you can view the ci build results of everest here a href http ci services fyfesoftware ca 8081 job everest 20community 20build http ci services fyfesoftware ca 8081 job everest 20community 20build a p p nbsp p div div class clearboth div | everest everest-framework architecture flexible mif ease transmission hl7v3-standards transport | os |
lara | lara web engine license apache 2 0 https img shields io badge license apache 2 0 blue https github com integrativesoft lara blob master license nuget version http img shields io nuget v integrative lara svg nocache 1 https www nuget org packages integrative lara download count https img shields io nuget dt integrative lara svg https www nuget org packages integrative lara build status https api travis ci com integrativesoft lara svg branch master https travis ci org integrativesoft lara coverage status https coveralls io repos github integrativesoft lara badge svg branch master lala 3 https coveralls io github integrativesoft lara branch master lara is a server side rendering framework for developing web user interfaces using c it is similar to server side blazor but is much more lightweight and easier to install for example while any type of blazor requires a whole sdk lara is just a nuget package scientificprogrammer net https scientificprogrammer net 2019 08 18 pros and cons of blazor for web development pagename pros and cons of blazor sample application csharp using integrative lara using system using system threading tasks namespace sampleapp public static class program public static async task main create and start application const int port 8182 using var app new application app publishpage new mycountercomponent value 5 await app start new startserveroptions port port print address on console var address http localhost port console writeline listening on address helper function to launch browser comment out as needed laraui launchbrowser address wait for asp net core shutdown await app waitforshutdown internal class mycountercomponent webcomponent private int value triggers propertychanged event public int value get value set setproperty ref value value public mycountercomponent shadowroot children new node new htmldivelement on propertychanged assigns innertext bind this x x innertext value tostring new htmlbuttonelement innertext increase event click value adding lara to an existing web server application to add lara to an existing asp net core server add to the startup class or equivalent csharp private readonly application laraapp new application public void configure iapplicationbuilder app app uselara laraapp new laraoptions configuration options creating desktop applications to create a desktop container for your web app here s a few options electron js https www electronjs org combined with electron cgi https github com ruidfigueiredo electron cgi readme library chromely https github com chromelyapps chromely neutralinojs https github com neutralinojs neutralinojs getting started there s no need to download this repository to use lara instead there s a nuget package https www nuget org packages integrative lara check out the wiki documentation https github com integrativesoft lara wiki how does lara work whenever the browser triggers a registered event e g click on a button it sends to the server a message saying that the button was clicked the server executes the code associated with the event manipulating the server s copy of the page and replies a json message with the delta between server and client how to contribute please send feedback issues questions suggestions requests for features and success stories please let me know by either opening an issue thank you if you like lara please give it a star it helps credits thanks to jetbrains https www jetbrains com from larawebengine for the licenses of rider and dotcover jetbrains support jetbrains svg https www jetbrains com from larawebengine | web cross-platform html5 web-development web-services web-components lara dotnet csharp ui | front_end |
ai_changelog | ai changelog license mit https img shields io badge license mit yellow svg https opensource org licenses mit python https img shields io badge python 3 7 3776ab svg style flat logo python logocolor white https www python org publish to pypi https github com joshuasundance swca ai changelog actions workflows publish on pypi yml badge svg https github com joshuasundance swca ai changelog actions workflows publish on pypi yml github tag with filter https img shields io github v tag joshuasundance swca ai changelog push to docker hub https github com joshuasundance swca ai changelog actions workflows docker hub yml badge svg https github com joshuasundance swca ai changelog actions workflows docker hub yml docker image size tag https img shields io docker image size joshuasundance ai changelog latest https hub docker com r joshuasundance ai changelog code climate maintainability https img shields io codeclimate maintainability joshuasundance swca ai changelog code climate issues https img shields io codeclimate issues joshuasundance swca ai changelog code climate technical debt https img shields io codeclimate tech debt joshuasundance swca ai changelog pre commit https img shields io badge pre commit enabled brightgreen logo pre commit logocolor white https github com pre commit pre commit ruff https img shields io endpoint url https raw githubusercontent com charliermarsh ruff main assets badge v1 json https github com charliermarsh ruff checked with mypy http www mypy lang org static mypy badge svg http mypy lang org code style black https img shields io badge code 20style black 000000 svg https github com psf black security bandit https img shields io badge security bandit yellow svg https github com pycqa bandit known vulnerabilities https snyk io test github joshuasundance swca ai changelog badge svg update ai changelog on push to main https github com joshuasundance swca ai changelog actions workflows ai changelog main push yml badge svg https github com joshuasundance swca ai changelog actions workflows ai changelog main push yml ai changelog is a python project that automatically generates changelog files summarizing code changes using ai it uses langchain https github com langchain ai langchain and openai https openai com models to analyze git commit diffs and generate natural language descriptions of the changes this allows maintaining an up to date changelog without manual effort this readme was originally written by claude an llm from anthropic usage bash usage ai changelog h provider openai anthropic anyscale model model temperature temperature max tokens max tokens hub prompt hub prompt context lines context lines max concurrency max concurrency v refs process command line arguments positional arguments refs reference comparison with standard git syntax options h help show this help message and exit provider openai anthropic anyscale model api provider model model model name temperature temperature model temperature max tokens max tokens max tokens in output hub prompt hub prompt prompt to pull from langchain hub context lines context lines number of context lines for each commit max concurrency max concurrency number of concurrent connections to llm provider 0 means no limit v verbose run langchain in verbose mode http github com joshuasundance swca ai changelog local install to generate a changelog locally bash pip install ai changelog ai changelog help ai changelog main head to summarize changes locally docker bash docker pull joshuasundance ai changelog latest docker run env file env v local repo dir container dir in repo w container dir in repo joshuasundance ai changelog latest main head github workflow the ai changelog main pr yml github workflows ai changelog main push yml workflow runs on pushes to main it generates summaries for the new commits and appends them to ai changelog md the updated file is then committed back to the pr branch bash ai changelog origin main origin main in a github action to summarize changes in response to a push to main ai changelog origin main head in a github action to summarize changes in response to a pr another flow was made to commit an updated changelog to an incoming pr before it was merged but that seemed less useful although it did work well configuration set environment variables as needed for your provider of choice default requires openai api key set langsmith environment variables to enable langsmith integration if applicable use command line arguments license this project is licensed under the mit license see the license license file for details todo testing get codellama working reliably in cicd currently hit or miss on structured output | changelog developer-tools documentation github langchain openai | ai |
grokking-system-design | grokking system design https www educative io collection 5668639101419520 5649050225344512 source educative https www educative io interview process scope the problem don t make assumptions ask clarifying questions to understand the constraints and use cases steps requirements clarifications system interface definition sketch up an abstract design building blocks of the system relationships between them steps back of the envelope estimation defining data model high level design identify and address the bottlenecks use the fundamental principles of scalable system design steps detailed design identifying and resolving bottlenecks distributed system design basics key characterics basics key characteristics md loading balancing basics load balancing md caching basics caching md sharding basics sharding md indexes basics indexes md proxies basics proxies md queues basics queues md redundancy basics redundancy md sql vs nosql basics sql vs nosql md cap theorem basics cap theorem md consistent hashing basics consistent hashing md client server communication basics client server communication md system designs short url service designs short url md pastebin designs pastebin md instagram designs instagram md dropbox designs dropbox md twitter designs twitter md youtube designs youtube md twitter search designs twitter search md web crawler designs web crawler md facebook newsfeed designs facebook newsfeed md yelp designs yelp md uber backend designs uber backend md ticketmaster designs ticketmaster md | os |
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IBMWatson-QA-Speech | ibmwatson qa speech node js application built using ibm bluemix that uses ibm watson services to answer health related questions using a voice interface services being used watson speech to text http www ibm com smarterplanet us en ibmwatson developercloud question answer html watson text to speech http www ibm com smarterplanet us en ibmwatson developercloud text to speech html watson question and answer http www ibm com smarterplanet us en ibmwatson developercloud speech to text html demo https watsonhealthqa mybluemix net give it a try click the button below to fork into ibm devops services and deploy your own copy of this application on bluemix deploy to bluemix https bluemix net deploy button png https bluemix net deploy repository https github com triceam ibmwatson qa speech browser requirements this requires html5 audio tag and getusermedia api mileage will vary if your browser does not support either one of these features most mobile browsers have issues with both of these you can see if your browser supports either of these features at http caniuse com feat stream http caniuse com feat audio license this sample code is licensed under apache 2 0 full license text is available in license license contributing see contributing contributing md open source ibm find more open source projects on the ibm github page http ibm github io original demo this is an updated demo assembled for ibm qa service original demo available at ibm watson cognitive computing speech apis http www tricedesigns com 2014 11 26 ibm watson cognitive computing speech apis additional details and video showing sample in action available at www tricedesigns com http www tricedesigns com 2015 04 01 ibm watson qa speech recognition speech synthesis a conversation with your computer | ai |
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CS352 | cs352 cs352 information technology it online spring 2021 during the covid 19 pandemic professor badri nath and goat ta david pham | server |
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generative-ai-examples | inspirations and examples for your next generative ai project this repository contains small examples using openai and probably other provides in the future looking for someone to kickstart your generative ai project write me a message jannis gansen codecamp n com and check out https www codecamp n com codecampn png logo png this repository will grow over time in case you encounter issues with examples feel free to raise an issue you probably should sign up at https openai com and get an api key before you start other than that we try to avoid additional service accounts trying out the examples you can either run the examples locally in jupyter notebook https jupyter org try or use a service like google colab https colab research google com current examples detect a throw away mail address try it in google colab https colab research google com github codecampn generative ai examples blob main examples detect throw away mail ipynb jupyter notebook examples detect throw away mail ipynb you don t want users from anonymous mail providers to register at your service but keeping a list of all providers is tedious use an autonomous agent to google a users domain and figure out whether it is a disposable mail provider query a document for example a german law for specific information try it in google colab https colab research google com github codecampn generative ai examples blob main examples query documents ipynb jupyter notebook examples query documents ipynb you have a law text and want your agent to respond to questions with the regulations defined in this law we ll use a vector database chroma that provides additional context for the agent | ai |
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FreeRTOS_Freemodbus_stm32_RTO_CRC | freertos dma uart freemodbus stm32 rto and crc hardware dma this is a modbus stm32 project using freemodbus freertos manage various of different tasks in order to achieve the maximum capability of stm32 hardware dma was used for diferent peripherals such as uart crc as rto receiver timeout in uart was used a modbus frame can be obtain through uart rto interrupt crc is used as well and dma will transfer data from uart receive memory to crc data register which can significantly reduce the cpu utilization for this project i use atollic truestudio as my ide and it is supposed to word on other gcc based ide such stm32cubeide and system workbench for stm32 my board is stm32f769i disco uart dma in this section i will explain how to use uart with dma to send and receive data uart dma send i set uart baud width as 115200 bits second stopbit 1 and parity check as odd be careful here the word length is set 9 bits this 9 bits is 8 bits plus parity bit for dma part i use normal mode the address of peripheral is fixed and the address of memory will increase at end of every dma cycle after initialize and link the uart and dma peripheral just call hal uart receive dma uart handletypedef huart uint8 t pdata uint16 t size to send data by dma uart dma receive the dma receiving scenario is different from sending every time uart sense data comes in dma will automatically move data into destination and not trigger interrupt the interrupt will only be triggered when the waiting time is over 32 bits 9 bits 3 5 31 5 bits round up to 32 bits in the uart rto interrupt the cpu will send a signal to tell the modbus task that a frame is ready as timeout receiving is automatically done by hardware programmer does not have to worry about write a timer interrupt to judge whether a frame is ready or not here is a flow chart shows difference between with rto and without rto rto bmp crc and dma crc is used to make sure there is no transmission error during transmission and stm32 has hardware crc and it is able to come out a result with few cycle in fact transferring data to crc data register will significantly reduce the usage of cpu for more information check the document using the crc peripheral in the stm32 family https www st com resource en application note dm00068118 using the crc peripheral in the stm32 family stmicroelectronics pdf in addition transferring data in dma from memory to crc data register is memory to memory transfer so it can be only done by dma2 in stm32 modbus because rto is used in this project i don t need the whole freemodbus framework i ported function parts of freemodbus into my project and it works well result communicate with pc software result png br left side is the message hex form from pc sending to stm32 and the right side is the message stm32 send back to pc todo port tcp into the project add some demos | os |
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datumaro | dataset management framework datumaro build status https github com openvinotoolkit datumaro actions workflows health check yml badge svg https github com openvinotoolkit datumaro actions workflows health check yml codecov https codecov io gh openvinotoolkit datumaro branch develop graph badge svg token fg25vu096q https codecov io gh openvinotoolkit datumaro a framework and cli tool to build transform and analyze datasets lint disable fenced code flag voc dataset annotation tool coco dataset datumaro dataset model training cvat annotations publication statistics etc lint enable fenced code flag getting started https openvinotoolkit github io datumaro latest docs get started quick start guide level up https openvinotoolkit github io datumaro latest docs level up basic skills features features user manual https openvinotoolkit github io datumaro latest docs user manual how to use datumaro developer manual https openvinotoolkit github io datumaro latest docs reference datumaro module contributing contributing features back to top dataset management framework datumaro dataset reading writing conversion in any direction cifar 10 100 https www cs toronto edu kriz cifar html classification cityscapes https www cityscapes dataset com coco http cocodataset org format data image info instances person keypoints captions labels panoptic stuff cvat https opencv github io cvat docs manual advanced xml format imagenet http image net org kitti http www cvlibs net datasets kitti index php segmentation detection 3d raw velodyne points labelme http labelme csail mit edu release3 0 lfw http vis www cs umass edu lfw classification person re identification landmarks mnist http yann lecun com exdb mnist classification open images https storage googleapis com openimages web download html pascal voc http host robots ox ac uk pascal voc voc2012 htmldoc index html classification detection segmentation action classification person layout tf detection api https github com tensorflow models blob master research object detection g3doc using your own dataset md bboxes masks yolo https github com alexeyab darknet how to train pascal voc data bboxes other formats and documentation for them can be found here https openvinotoolkit github io datumaro latest docs data formats supported formats dataset building merging multiple datasets into one dataset filtering by a custom criteria remove polygons of a certain class remove images without annotations of a specific class remove occluded annotations from images keep only vertically oriented images remove small area bounding boxes from annotations annotation conversions for instance polygons to instance masks and vice versa apply a custom colormap for mask annotations rename or remove dataset labels splitting a dataset into multiple subsets like train val and test random split task specific splits based on annotations which keep initial label and attribute distributions for classification task based on labels for detection task based on bboxes for re identification task based on labels avoiding having same ids in training and test splits sampling a dataset analyzes inference result from the given dataset and selects the best and the least amount of samples for annotation select the sample that best suits model training sampling with entropy based algorithm dataset quality checking simple checking for errors comparison with model inference merging and comparison of multiple datasets annotation validation based on the task type classification etc dataset comparison dataset statistics image mean and std annotation statistics model integration inference openvino caffe pytorch tensorflow mxnet etc explainable ai rise algorithm https arxiv org abs 1806 07421 rise for classification rise for object detection check the design document https openvinotoolkit github io datumaro latest docs explanation architecture for a full list of features check the user manual https openvinotoolkit github io datumaro latest docs user manual how to use datumaro for usage instructions contributing back to top dataset management framework datumaro feel free to open an issue https github com openvinotoolkit datumaro issues new if you think something needs to be changed you are welcome to participate in development instructions are available in our contribution guide https github com openvinotoolkit datumaro blob develop contributing md telemetry data collection note the openvino telemetry library https github com openvinotoolkit telemetry is used to collect basic information about datumaro usage to enable disable telemetry data collection please see the guide https openvinotoolkit github io datumaro latest docs user manual how to control tm data collection | deep-learning neural-networks openvino-toolkit computer-vision datasets format-converter dataset coco imagenet pascal-voc yolo | ai |
Ultimate-ASP.NET-5-Web-API-Development-Guide- | ultimate asp net 5 web api development guide ultimate asp net 5 web api development guide published by packt | front_end |
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volo | volo http volojs org create browser based front end projects from project templates and add dependencies by fetching them from github once your project is set up automate common tasks volo is dependency manager and project creation tool that favors github for the package repository at its heart volo is a generic command runner you can create new commands for volo and you can use commands others have created by default volo knows how to create a new web project https github com volojs volo blob master commands create doc md add scripts for a web project from the command line https github com volojs volo blob master commands add doc md automate project actions via volofiles https github com volojs volo wiki creating a volofile and reusable volo commands https github com volojs volo wiki creating a volo command prerequisites node http nodejs org 0 6 5 or later installed if you are using ubuntu then you may need to apt get install nodejs legacy too install volo requires node to run node includes npm http npmjs org a package manager for node code to install volo npm install g volo if you get an error when running that command and it contains this line somewhere in it npm err please try running this command again as root administrator you will need to run the install via sudo sudo npm install g volo usage volo can use github to retrieve code so one of the core concepts when using it is understanding user repo for archive names see the add doc https github com volojs volo blob master commands add doc md for more info on the types of archive names to use amd project example to set up an amd requirejs based project called fast that uses amd versions of backbone jquery and underscore volo create fast uses volojs create template https github com volojs create template for project template cd fast volo add jquery uses jquery jquery as the repo volo add underscore uses amdjs underscore as repo since an amd project volo add backbone uses amdjs backbone as repo since an amd project then modify www js app js to require the modules you need and add your app logic the above example uses the amdjs underscore https github com amdjs underscore and amdjs backbone https github com amdjs backbone versions of those libraries which include integrated amd support browser globals project example to set up an html5 boilerplate project that does not use amd requirejs but does use documentcloud repos of backbone and underscore the boilerplate already has jquery volo create html5fast html5 boilerplate pulls down latest tag of that repo cd html5fast volo add underscore uses documentcloud underscore as repo volo add backbone uses documentcloud backbone as repo updating a previously added library there is no update command in volo however updating a library is simple volo add f underscore this will delete your local copy of underscore and then re add underscore library best practices to work well with volo here are some tips on how to structure your library code library best practices https github com volojs volo wiki library best practices details design goals https github com volojs volo wiki design goals prior art https github com volojs volo wiki prior art npm cpm bpm create a volo command https github com volojs volo wiki creating a volo command create a volofile https github com volojs volo wiki creating a volofile license mit and new bsd https github com volojs volo blob master license engage discussion list http groups google com group volojs file an issue https github com volojs volo issues working with the volo code https github com volojs volo blob master docs workingwithcode md | front_end |
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Full-Stack-Web-Development-with-Flask | full stack web development with flask full stack web development with flask published by packt | front_end |
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iot-device-sdk-embedded-c | status inactive https img shields io badge status inactive red svg this project is no longer actively developed or maintained google cloud iot core is being retired on august 16 2023 contact your google cloud account team for more information additional guidance can be found here https cloud google com iot core google cloud iot device sdk for embedded c the google cloud iot device sdk for embedded c is an easy to port open source c library that connects low end iot devices to google cloud iot core the device sdk supports concurrent pub sub traffic on a non blocking socket implementation that runs on posix rtos and no os devices a board support package bsp facilitates portability and provides platform specific implementations through a set of functions and directories the bsp helps implement crypto and time functions networking transport layer security tls memory management and random number generation without working through mqtt internals for more details see the user guide in the docs directory source to get the source clone from the master branch of the google cloud iot device sdk for embedded c github repository https github com googlecloudplatform iot device sdk embedded c git git clone https github com googlecloudplatform iot device sdk embedded c git recurse submodules directory structure bin executables and libraries produced by a build doc doc documentation doxygen references user guide and porting guide examples examples example source with makefiles after you build with make this directory will also contain the example executables include include header files of the device sdk api you must add this directory to the header include path when compiling your application against the source include bsp include bsp header files of the board support package bsp functions declared here must be defined in a device specific bsp implementation when compiling your bsp source make sure this directory is on the include path make make build system configuration files obj object files generated during a build res res resource files for example trusted root ca certificates src src the source files of the device sdk a bsp implementation is provided for posix third party third party third party open source components tools tools scripts used by the maintainers of the repository building the default build tool for the device sdk is make it invokes gcc https www gnu org software gcc to produce a native build on a posix host this serves as the default development environment on ubuntu run the following command to build the device sdk make the source can be cross compiled to other target platforms via custom toolchains and the makefile or with a specific device sdk s ide for more information see the porting guide doc porting guide md building a tls static library by default the device sdk is built with secure connection support and thus requires a third party tls implementation to link against when executing make the build system defaults to mbedtls as a result the make and make iotc bsp tls mbedtls commands are synonymous you can also configure the make system to build a library that uses wolfssl make clean make iotc bsp tls wolfssl the value of iotc bsp tls determines which script is run mbedtls res tls build mbedtls sh res tls build mbedtls sh wolfssl res tls build wolfssl sh res tls build wolfssl sh the mbedtls build script includes a git clone and branch checkout of the mbedtls source upon confirmation of the license agreement however the wolfssl build script requires you to clone the repository yourself when you run make iotc bsp tls wolfssl instructions are provided for cloning the repository for more details on running the scripts see security security building and executing tests to build and execute all tests 1 run git submodule init from the project s root directory to initialize all test dependencies 1 run git submodule update from the project s root directory to clone all submodules 1 run make tests by default test execution is the final step of the tests build process you can also execute the tests manually cd bin host os tests iotc utests iotc gtests iotc itests building the examples before building the examples build both the device sdk static library and a tls library as described in the preceding sections then complete the steps below to run the examples 1 create a project registry and device in cloud iot core 2 create cloud iot core device credentials https cloud google com iot docs how tos credentials keys 3 follow the steps in the examples readme md files to provision the device credentials and build the client applications 4 run make in the examples examples folder the make process automatically downloads the google root ca pem file to the example directories the file enables tls when communicating with cloud iot core to securely connect to cloud iot core a root ca pem file must be in the current working directory of the example executables by default the file is in res trusted rootca certs roots pem and contains two certificates that validate cloud iot core credentials the make process automatically moves this file from res trusted rootca certs roots pem to the correct location to maintain a secure connection with cloud iot core we strongly recommend that you perform frequent security related firmware updates cross compilation follow the steps below to perform the cross compilation process extend the build system with a new cross compilation preset in the file make mt config mt presets mk create a set of files that represent the board support package bsp implementation you ve written for your platform store these in the directory src bsp platform target platform build a tls bsp implementation to invoke the tls sdk for your platform store these in a new directory src bsp tls target tls solution build a cryptography bsp implementation to handle key signatures of jwts on your target platform in the directory src bsp crypto target crypto soluction for more details on the cross compilation process see the porting guide doc porting guide md security the device sdk supports secure connection through a third party tls library the device sdk is tested against mbedtls https tls mbed org and wolfssl https www wolfssl com this repository does not directly include tls libraries you can clone the tls git repositories and place them in the third party tls mbedtls and third party tls wolfssl directories respectively running make without any parameters will start a build that includes git checkout build configuration and compilation of the mbedtls library the device sdk supports other tls libraries through the bsp tls api for information about configuring the build process to work with your preferred library see the porting guide in doc porting guide md additionally check the user guide doc user guide md to make sure your tls implementation meets the security requirements to connect to cloud iot core stability and qa 19 combinations of compilers and feature sets are continuously built 58 functional 23 integration and 199 unit tests are executed after each build tests are executed against the tls libraries mbedtls https tls mbed org and wolfssl https www wolfssl com branch build status master build status travis badge travis url travis badge https travis ci com googlecloudplatform iot device sdk embedded c svg branch master travis url https travis ci com googlecloudplatform iot device sdk embedded c contributing for information about contributing to this repository see contributing md contributing md learn more review the following documentation doc user guide md doc user guide md user guide that covers device sdk features and usage doc porting guide md doc porting guide md porting guide that provides information about porting the device sdk to target devices device sdk api https googlecloudplatform github io iot device sdk embedded c api html and bsp https googlecloudplatform github io iot device sdk embedded c bsp html references license copyright 2018 2020 google llc licensed under the bsd 3 clause license for more information see license md license md | server |
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Mallet | build status https travis ci com mncc mallet svg branch master https travis ci com mncc mallet codecov https codecov io gh mncc mallet branch master graph badge svg https codecov io gh mncc mallet mallet website https mimno github io mallet mallet is a java based package for statistical natural language processing document classification clustering topic modeling information extraction and other machine learning applications to text mallet includes sophisticated tools for document classification efficient routines for converting text to features a wide variety of algorithms including na ve bayes maximum entropy and decision trees and code for evaluating classifier performance using several commonly used metrics in addition to classification mallet includes tools for sequence tagging for applications such as named entity extraction from text algorithms include hidden markov models maximum entropy markov models and conditional random fields these methods are implemented in an extensible system for finite state transducers topic models are useful for analyzing large collections of unlabeled text the mallet topic modeling toolkit contains efficient sampling based implementations of latent dirichlet allocation pachinko allocation and hierarchical lda many of the algorithms in mallet depend on numerical optimization mallet includes an efficient implementation of limited memory bfgs among many other optimization methods in addition to sophisticated machine learning applications mallet includes routines for transforming text documents into numerical representations that can then be processed efficiently this process is implemented through a flexible system of pipes which handle distinct tasks such as tokenizing strings removing stopwords and converting sequences into count vectors an add on package to mallet called grmm contains support for inference in general graphical models and training of crfs with arbitrary graphical structure installation to build a mallet 2 0 development release you must have the apache ant build tool installed from the command prompt first change to the mallet directory and then type ant if ant finishes with build successful mallet is now ready to use if you would like to deploy mallet as part of a larger application it is helpful to create a single jar file that contains all of the compiled code once you have compiled the individual mallet class files use the command ant jar this process will create a file mallet jar in the dist directory within mallet usage once you have installed mallet you can use it using the following command bin mallet command option value option value type bin mallet to get a list of commands and use the option help with any command to get a description of valid options for details about the commands please visit the api documentation and website at https mimno github io mallet list of algorithms topic modelling lda parallel lda dmr lda hierarchical lda labeled lda polylingual topic model hierarchical pachinko allocation model pam weighted topic model lda with integrated phrase discovery word embeddings word2vec using skip gram with negative sampling classification adaboost bagging winnow c45 decision tree ensemble trainer maximum entropy classifier multinomial logistic regression naive bayes rank maximum entropy classifier posterior regularization auxiliary model clustering greedy agglomerative hill climbing k means k best sequence prediction models conditional random fields maximum entropy markov models hidden markov models semi supervised sequence prediction models linear regression | ai |
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Machine-Learning-Tutorials | machine learning deep learning tutorials awesome https cdn rawgit com sindresorhus awesome d7305f38d29fed78fa85652e3a63e154dd8e8829 media badge svg https github com sindresorhus awesome this repository contains a topic wise curated list of machine learning and deep learning tutorials articles and other resources other awesome lists can be found in this list https github com sindresorhus awesome if you want to contribute to this list please read contributing guidelines https github com ujjwalkarn machine learning tutorials blob master contributing md curated list of r tutorials for data science nlp and machine learning https github com ujjwalkarn datasciencer curated list of python tutorials for data science nlp and machine learning https github com ujjwalkarn datasciencepython contents introduction general interview resources interview artificial intelligence ai genetic algorithms ga statistics stat useful blogs blogs resources on quora quora resources on kaggle kaggle cheat sheets cs classification classification linear regression linear logistic regression logistic model validation using resampling validation cross validation cross bootstraping boot deep learning deep frameworks frame feed forward networks feed recurrent neural nets lstm gru rnn restricted boltzmann machine dbns rbm autoencoders auto convolutional neural nets cnn graph representation learning nrl natural language processing nlp topic modeling lda topic word2vec word2vec computer vision vision support vector machine svm reinforcement learning rl decision trees dt random forest bagging rf boosting gbm ensembles ensem stacking models stack vc dimension vc bayesian machine learning bayes semi supervised learning semi optimizations opt other useful tutorials other a name general introduction machine learning course by andrew ng stanford university https www coursera org learn machine learning ai ml youtube courses https github com dair ai ml youtube courses curated list of machine learning resources https hackr io tutorials learn machine learning ml in depth introduction to machine learning in 15 hours of expert videos http www dataschool io 15 hours of expert machine learning videos an introduction to statistical learning http www bcf usc edu gareth isl list of machine learning university courses https github com prakhar1989 awesome courses machine learning machine learning for software engineers https github com zuzoovn machine learning for software engineers dive into machine learning https github com hangtwenty dive into machine learning a curated list of awesome machine learning frameworks libraries and software https github com josephmisiti awesome machine learning a curated list of awesome data visualization libraries and resources https github com fasouto awesome dataviz an awesome data science repository to learn and apply for real world problems https github com okulbilisim awesome datascience the open source data science masters http datasciencemasters org machine learning faqs on cross validated http stats stackexchange com questions tagged machine learning machine learning algorithms that you should always have a strong understanding of https www quora com what are some machine learning algorithms that you should always have a strong understanding of and why difference between linearly independent orthogonal and uncorrelated variables http terpconnect umd edu bmomen biom621 lineardepcorrorthogonal pdf list of machine learning concepts https en wikipedia org wiki list of machine learning concepts slides on several machine learning topics http www slideshare net pierluca lanzi presentations mit machine learning lecture slides http www ai mit edu courses 6 867 f04 lectures html comparison supervised learning algorithms http www dataschool io comparing supervised learning algorithms learning data science fundamentals http www dataschool io learning data science fundamentals machine learning mistakes to avoid https medium com nomadic mind new to machine learning avoid these three mistakes 73258b3848a4 lih061l3l statistical machine learning course http www stat cmu edu larry sml theanalyticsedge edx notes and codes https github com pedrosan theanalyticsedge have fun with machine learning https github com humphd have fun with machine learning twitter s most shared machinelearning content from the past 7 days http theherdlocker com tweet popularity machinelearning grokking machine learning https www manning com books grokking machine learning a name interview interview resources 41 essential machine learning interview questions with answers https www springboard com blog machine learning interview questions how can a computer science graduate student prepare himself for data scientist interviews https www quora com how can a computer science graduate student prepare himself for data scientist machine learning intern interviews how do i learn machine learning https www quora com how do i learn machine learning 1 faqs about data science interviews https www quora com topic data science interviews faq what are the key skills of a data scientist https www quora com what are the key skills of a data scientist the big list of ds ml interview resources https towardsdatascience com the big list of ds ml interview resources 2db4f651bd63 a name ai artificial intelligence awesome artificial intelligence github repo https github com owainlewis awesome artificial intelligence uc berkeley cs188 intro to ai http ai berkeley edu home html lecture videos http ai berkeley edu lecture videos html 2 https www youtube com watch v w1s hsakptm programming community curated resources for learning artificial intelligence https hackr io tutorials learn artificial intelligence ai mit 6 034 artificial intelligence lecture videos https www youtube com playlist list plul4u3cngp63gfhb6xb kvbiqhye 4hsi complete course https ocw mit edu courses electrical engineering and computer science 6 034 artificial intelligence fall 2010 edx course klein abbeel https courses edx org courses berkeleyx cs188x 1 1t2013 info udacity course norvig thrun https www udacity com course intro to artificial intelligence cs271 ted talks on ai http www ted com playlists 310 talks on artificial intelligen a name ga genetic algorithms genetic algorithms wikipedia page https en wikipedia org wiki genetic algorithm simple implementation of genetic algorithms in python part 1 http outlace com miniga html part 2 http outlace com miniga addendum html genetic algorithms vs artificial neural networks http stackoverflow com questions 1402370 when to use genetic algorithms vs when to use neural networks genetic algorithms explained in plain english http www ai junkie com ga intro gat1 html genetic programming https en wikipedia org wiki genetic programming genetic programming in python github https github com trevorstephens gplearn genetic alogorithms vs genetic programming quora https www quora com whats the difference between genetic algorithms and genetic programming stackoverflow http stackoverflow com questions 3819977 what are the differences between genetic algorithms and genetic programming a name stat statistics stat trek website http stattrek com a dedicated website to teach yourselves statistics learn statistics using python https github com rouseguy intro2stats learn statistics using an application centric programming approach statistics for hackers slides jakevdp https speakerdeck com jakevdp statistics for hackers slides by jake vanderplas online statistics book http onlinestatbook com 2 index html an interactive multimedia course for studying statistics what is a sampling distribution http stattrek com sampling sampling distribution aspx tutorials ap statistics tutorial http stattrek com tutorials ap statistics tutorial aspx statistics and probability tutorial http stattrek com tutorials statistics tutorial aspx matrix algebra tutorial http stattrek com tutorials matrix algebra tutorial aspx what is an unbiased estimator https www physicsforums com threads what is an unbiased estimator 547728 goodness of fit explained https en wikipedia org wiki goodness of fit what are qq plots http onlinestatbook com 2 advanced graphs q q plots html openintro statistics https www openintro org stat textbook php stat book os free pdf textbook a name blogs useful blogs edwin chen s blog http blog echen me a blog about math stats ml crowdsourcing data science the data school blog http www dataschool io data science for beginners ml wave http mlwave com a blog for learning machine learning andrej karpathy http karpathy github io a blog about deep learning and data science in general colah s blog http colah github io awesome neural networks blog alex minnaar s blog http alexminnaar com a blog about machine learning and software engineering statistically significant http andland github io andrew landgraf s data science blog simply statistics http simplystatistics org a blog by three biostatistics professors yanir seroussi s blog https yanirseroussi com a blog about data science and beyond fastml http fastml com machine learning made easy trevor stephens blog http trevorstephens com trevor stephens personal page no free hunch kaggle http blog kaggle com the kaggle blog about all things data science a quantitative journey outlace http outlace com learning quantitative applications r4stats http r4stats com analyze the world of data science and to help people learn to use r variance explained http varianceexplained org david robinson s blog ai junkie http www ai junkie com a blog about artificial intellingence deep learning blog by tim dettmers http timdettmers com making deep learning accessible j alammar s blog http jalammar github io blog posts about machine learning and neural nets adam geitgey https medium com ageitgey machine learning is fun 80ea3ec3c471 f7vwrtfne easiest introduction to machine learning ethen s notebook collection https github com ethen8181 machine learning continuously updated machine learning documentations mainly in python3 contents include educational implementation of machine learning algorithms from scratch and open source library usage a name quora resources on quora most viewed machine learning writers https www quora com topic machine learning writers data science topic on quora https www quora com data science william chen s answers https www quora com william chen 6 answers michael hochster s answers https www quora com michael hochster answers ricardo vladimiro s answers https www quora com ricardo vladimiro 1 answers storytelling with statistics https datastories quora com data science faqs on quora https www quora com topic data science faq machine learning faqs on quora https www quora com topic machine learning faq a name kaggle kaggle competitions writeup how to almost win kaggle competitions https yanirseroussi com 2014 08 24 how to almost win kaggle competitions convolution neural networks for eeg detection http blog kaggle com 2015 10 05 grasp and lift eeg detection winners interview 3rd place team hedj facebook recruiting iii explained http alexminnaar com tag kaggle competitions html predicting ctr with online ml http mlwave com predicting click through rates with online machine learning how to rank 10 in your first kaggle competition https dnc1994 com 2016 05 rank 10 percent in first kaggle competition en a name cs cheat sheets probability cheat sheet http static1 squarespace com static 54bf3241e4b0f0d81bf7ff36 t 55e9494fe4b011aed10e48e5 1441352015658 probability cheatsheet pdf source http www wzchen com probability cheatsheet machine learning cheat sheet https github com soulmachine machine learning cheat sheet ml compiled https ml compiled readthedocs io en latest a name classification classification does balancing classes improve classifier performance http www win vector com blog 2015 02 does balancing classes improve classifier performance what is deviance http stats stackexchange com questions 6581 what is deviance specifically in cart rpart when to choose which machine learning classifier http stackoverflow com questions 2595176 when to choose which machine learning classifier what are the advantages of different classification algorithms https www quora com what are the advantages of different classification algorithms roc and auc explained http www dataschool io roc curves and auc explained related video https youtu be oal6eayp yo an introduction to roc analysis https ccrma stanford edu workshops mir2009 references rocintro pdf simple guide to confusion matrix terminology http www dataschool io simple guide to confusion matrix terminology a name linear linear regression general general assumptions of linear regression http pareonline net getvn asp n 2 v 8 stack exchange http stats stackexchange com questions 16381 what is a complete list of the usual assumptions for linear regression linear regression comprehensive resource http people duke edu rnau regintro htm applying and interpreting linear regression http www dataschool io applying and interpreting linear regression what does having constant variance in a linear regression model mean http stats stackexchange com questions 52089 what does having constant variance in a linear regression model mean 52107 stw 2 52107 difference between linear regression on y with x and x with y http stats stackexchange com questions 22718 what is the difference between linear regression on y with x and x with y lq 1 is linear regression valid when the dependant variable is not normally distributed https www researchgate net post is linear regression valid when the outcome dependant variable not normally distributed multicollinearity and vif dummy variable trap multicollinearity https en wikipedia org wiki multicollinearity dealing with multicollinearity using vifs https jonlefcheck net 2012 12 28 dealing with multicollinearity using variance inflation factors residual analysis residuals interpreting plot lm in r http stats stackexchange com questions 58141 interpreting plot lm how to interpret a qq plot http stats stackexchange com questions 101274 how to interpret a qq plot lq 1 interpreting residuals vs fitted plot http stats stackexchange com questions 76226 interpreting the residuals vs fitted values plot for verifying the assumptions outliers outliers how should outliers be dealt with http stats stackexchange com questions 175 how should outliers be dealt with in linear regression analysis elastic net https en wikipedia org wiki elastic net regularization regularization and variable selection via the elastic net https web stanford edu hastie papers elasticnet pdf a name logistic logistic regression logistic regression wiki https en wikipedia org wiki logistic regression geometric intuition of logistic regression http florianhartl com logistic regression geometric intuition html obtaining predicted categories choosing threshold http stats stackexchange com questions 25389 obtaining predicted values y 1 or 0 from a logistic regression model fit residuals in logistic regression http stats stackexchange com questions 1432 what do the residuals in a logistic regression mean difference between logit and probit models http stats stackexchange com questions 20523 difference between logit and probit models 30909 logistic regression wiki https en wikipedia org wiki logistic regression probit model wiki https en wikipedia org wiki probit model pseudo r2 for logistic regression http stats stackexchange com questions 3559 which pseudo r2 measure is the one to report for logistic regression cox s how to calculate http stats stackexchange com questions 8511 how to calculate pseudo r2 from rs logistic regression other details http www ats ucla edu stat mult pkg faq general psuedo rsquareds htm guide to an in depth understanding of logistic regression http www dataschool io guide to logistic regression a name validation model validation using resampling resampling explained https en wikipedia org wiki resampling statistics partioning data set in r http stackoverflow com questions 13536537 partitioning data set in r based on multiple classes of observations implementing hold out validaion in r http stackoverflow com questions 22972854 how to implement a hold out validation in r 2 http www gettinggeneticsdone com 2011 02 split data frame into testing and html a name cross cross validation https en wikipedia org wiki cross validation statistics how to use cross validation in predictive modeling http stuartlacy co uk 2016 02 04 how to correctly use cross validation in predictive modelling training with full dataset after cv http stats stackexchange com questions 11602 training with the full dataset after cross validation which cv method is best http stats stackexchange com questions 103459 how do i know which method of cross validation is best variance estimates in k fold cv http stats stackexchange com questions 31190 variance estimates in k fold cross validation is cv a subsitute for validation set http stats stackexchange com questions 18856 is cross validation a proper substitute for validation set choice of k in k fold cv http stats stackexchange com questions 27730 choice of k in k fold cross validation cv for ensemble learning http stats stackexchange com questions 102631 k fold cross validation of ensemble learning k fold cv in r http stackoverflow com questions 22909197 creating folds for k fold cv in r using caret good resources http www chioka in tag cross validation overfitting and cross validation preventing overfitting the cross validation data andrew ng http ai stanford edu ang papers cv final pdf over fitting in model selection and subsequent selection bias in performance evaluation http www jmlr org papers volume11 cawley10a cawley10a pdf cv for detecting and preventing overfitting http www autonlab org tutorials overfit10 pdf how does cv overcome the overfitting problem http stats stackexchange com questions 9053 how does cross validation overcome the overfitting problem a name boot bootstrapping https en wikipedia org wiki bootstrapping statistics why bootstrapping works http stats stackexchange com questions 26088 explaining to laypeople why bootstrapping works good animation https www stat auckland ac nz wild bootanim example of bootstapping http statistics about com od applications a example of bootstrapping htm understanding bootstapping for validation and model selection http stats stackexchange com questions 14516 understanding bootstrapping for validation and model selection rq 1 cross validation vs bootstrap to estimate prediction error http stats stackexchange com questions 18348 differences between cross validation and bootstrapping to estimate the predictio cross validation vs 632 bootstrapping to evaluate classification performance http stats stackexchange com questions 71184 cross validation or bootstrapping to evaluate classification performance a name deep deep learning fast ai practical deep learning for coders http course fast ai fast ai cutting edge deep learning for coders http course fast ai part2 html a curated list of awesome deep learning tutorials projects and communities https github com christoschristofidis awesome deep learning deep learning papers reading roadmap https github com floodsung deep learning papers reading roadmap blob master readme md lots of deep learning resources http deeplearning4j org documentation html interesting deep learning and nlp projects stanford http cs224d stanford edu reports html website http cs224d stanford edu core concepts of deep learning https devblogs nvidia com parallelforall deep learning nutshell core concepts understanding natural language with deep neural networks using torch https devblogs nvidia com parallelforall understanding natural language deep neural networks using torch stanford deep learning tutorial http ufldl stanford edu tutorial deep learning faqs on quora https www quora com topic deep learning faq google deep learning page https plus google com communities 112866381580457264725 recent reddit amas related to deep learning http deeplearning net 2014 11 22 recent reddit amas about deep learning another ama https www reddit com r iama comments 3mdk9v we are google researchers working on deep where to learn deep learning http www kdnuggets com 2014 05 learn deep learning courses tutorials overviews html deep learning nvidia concepts http devblogs nvidia com parallelforall deep learning nutshell core concepts introduction to deep learning using python github https github com rouseguy intro2deeplearning good introduction slides https speakerdeck com bargava introduction to deep learning video lectures oxford 2015 https www youtube com playlist list ple6wd9fr efw8dtjaupotupcqmov53fu video lectures summer school montreal http videolectures net deeplearning2015 montreal deep learning software list http deeplearning net software links hacker s guide to neural nets http karpathy github io neuralnets top arxiv deep learning papers explained http www kdnuggets com 2015 10 top arxiv deep learning papers explained html geoff hinton youtube vidoes on deep learning https www youtube com watch v icomkxaw5va awesome deep learning reading list http deeplearning net reading list deep learning comprehensive website http deeplearning net software http deeplearning net software links deeplearning tutorials http deeplearning4j org awesome deep learning tutorial https www toptal com machine learning an introduction to deep learning from perceptrons to deep networks deep learning basics http alexminnaar com deep learning basics neural networks backpropagation and stochastic gradient descent html intuition behind backpropagation https medium com spidernitt breaking down neural networks an intuitive approach to backpropagation 3b2ff958794c stanford tutorials http ufldl stanford edu tutorial supervised multilayerneuralnetworks train validation test in artificial neural networks http stackoverflow com questions 2976452 whats is the difference between train validation and test set in neural networ artificial neural networks tutorials http stackoverflow com questions 478947 what are some good resources for learning about artificial neural networks neural networks faqs on stack overflow http stackoverflow com questions tagged neural network sort votes pagesize 50 deep learning tutorials on deeplearning net http deeplearning net tutorial index html neural networks and deep learning online book http neuralnetworksanddeeplearning com neural machine translation machine translation reading list https github com thunlp mt mt reading list machine translation reading list introduction to neural machine translation with gpus part 1 https devblogs nvidia com parallelforall introduction neural machine translation with gpus part 2 https devblogs nvidia com parallelforall introduction neural machine translation gpus part 2 part 3 https devblogs nvidia com parallelforall introduction neural machine translation gpus part 3 deep speech accurate speech recognition with gpu accelerated deep learning https devblogs nvidia com parallelforall deep speech accurate speech recognition gpu accelerated deep learning a name frame deep learning frameworks torch vs theano http fastml com torch vs theano dl4j vs torch7 vs theano http deeplearning4j org compare dl4j torch7 pylearn html deep learning libraries by language http www teglor com b deep learning libraries language cm569 theano https en wikipedia org wiki theano software website http deeplearning net software theano theano introduction http www wildml com 2015 09 speeding up your neural network with theano and the gpu theano tutorial http outlace com beginner tutorial theano good theano tutorial http deeplearning net software theano tutorial logistic regression using theano for classifying digits http deeplearning net tutorial logreg html logreg mlp using theano http deeplearning net tutorial mlp html mlp cnn using theano http deeplearning net tutorial lenet html lenet rnns using theano http deeplearning net tutorial rnnslu html rnnslu lstm for sentiment analysis in theano http deeplearning net tutorial lstm html lstm rbm using theano http deeplearning net tutorial rbm html rbm dbns using theano http deeplearning net tutorial dbn html dbn all codes https github com lisa lab deeplearningtutorials deep learning implementation tutorials keras and lasagne https github com vict0rsch deep learning torch http torch ch torch ml tutorial http code madbits com wiki doku php code https github com torch tutorials intro to torch http ml informatik uni freiburg de media teaching ws1415 presentation dl lect3 pdf learning torch github repo https github com chetannaik learning torch awesome torch repository on github https github com carpedm20 awesome torch machine learning using torch oxford univ https www cs ox ac uk people nando defreitas machinelearning code https github com oxford cs ml 2015 torch internals overview https apaszke github io torch internals html torch cheatsheet https github com torch torch7 wiki cheatsheet understanding natural language with deep neural networks using torch http devblogs nvidia com parallelforall understanding natural language deep neural networks using torch caffe deep learning for computer vision with caffe and cudnn https devblogs nvidia com parallelforall deep learning computer vision caffe cudnn tensorflow website http tensorflow org tensorflow examples for beginners https github com aymericdamien tensorflow examples stanford tensorflow for deep learning research course https web stanford edu class cs20si syllabus html github repo https github com chiphuyen tf stanford tutorials simplified scikit learn style interface to tensorflow https github com tensorflow skflow learning tensorflow github repo https github com chetannaik learning tensorflow benchmark tensorflow github https github com soumith convnet benchmarks issues 66 awesome tensorflow list https github com jtoy awesome tensorflow tensorflow book https github com binroot tensorflow book android tensorflow machine learning example https blog mindorks com android tensorflow machine learning example ff0e9b2654cc github repo https github com mindorksopensource androidtensorflowmachinelearningexample creating custom model for android using tensorflow https blog mindorks com creating custom model for android using tensorflow 3f963d270bfb github repo https github com mindorksopensource androidtensorflowmnistexample a name feed feed forward networks a quick introduction to neural networks https ujjwalkarn me 2016 08 09 quick intro neural networks implementing a neural network from scratch http www wildml com 2015 09 implementing a neural network from scratch code https github com dennybritz nn from scratch speeding up your neural network with theano and the gpu http www wildml com 2015 09 speeding up your neural network with theano and the gpu code https github com dennybritz nn theano basic ann theory https takinginitiative wordpress com 2008 04 03 basic neural network tutorial theory role of bias in neural networks http stackoverflow com questions 2480650 role of bias in neural networks choosing number of hidden layers and nodes http stackoverflow com questions 3345079 estimating the number of neurons and number of layers of an artificial neural ne 2 http stackoverflow com questions 10565868 multi layer perceptron mlp architecture criteria for choosing number of hidde lq 1 3 http stackoverflow com questions 9436209 how to choose number of hidden layers and nodes in neural network 2 backpropagation in matrix form http sudeepraja github io neural ann implemented in c ai junkie http www ai junkie com ann evolved nnt6 html simple implementation http stackoverflow com questions 15395835 simple multi layer neural network implementation nn for beginners http www codeproject com articles 16419 ai neural network for beginners part of regression and classification with nns slides http www autonlab org tutorials neural13 pdf another intro http www doc ic ac uk nd surprise 96 journal vol4 cs11 report html a name rnn recurrent and lstm networks awesome rnn list of resources github repo https github com kjw0612 awesome rnn recurrent neural net tutorial part 1 http www wildml com 2015 09 recurrent neural networks tutorial part 1 introduction to rnns part 2 http www wildml com 2015 09 recurrent neural networks tutorial part 2 implementing a language model rnn with python numpy and theano part 3 http www wildml com 2015 10 recurrent neural networks tutorial part 3 backpropagation through time and vanishing gradients code https github com dennybritz rnn tutorial rnnlm nlp rnn representations http colah github io posts 2014 07 nlp rnns representations the unreasonable effectiveness of rnns http karpathy github io 2015 05 21 rnn effectiveness torch code https github com karpathy char rnn python code https gist github com karpathy d4dee566867f8291f086 intro to rnn http deeplearning4j org recurrentnetwork html lstm http deeplearning4j org lstm html an application of rnn http hackaday com 2015 10 15 73 computer scientists created a neural net and you wont believe what happened next optimizing rnn performance http svail github io simple rnn http outlace com simple recurrent neural network auto generating clickbait with rnn https larseidnes com 2015 10 13 auto generating clickbait with recurrent neural networks sequence learning using rnn slides http www slideshare net indicods general sequence learning with recurrent neural networks for next ml machine translation using rnn paper http emnlp2014 org papers pdf emnlp2014179 pdf music generation using rnns keras https github com mattvitelli gruv using rnn to create on the fly dialogue keras http neuralniche com post tutorial long short term memory lstm understanding lstm networks http colah github io posts 2015 08 understanding lstms lstm explained https apaszke github io lstm explained html beginner s guide to lstm http deeplearning4j org lstm html implementing lstm from scratch http www wildml com 2015 10 recurrent neural network tutorial part 4 implementing a grulstm rnn with python and theano python theano code https github com dennybritz rnn tutorial gru lstm torch code for character level language models using lstm https github com karpathy char rnn lstm for kaggle eeg detection competition torch code https github com apaszke kaggle grasp and lift lstm for sentiment analysis in theano http deeplearning net tutorial lstm html lstm deep learning for visual q a lstm cnn http avisingh599 github io deeplearning visual qa code https github com avisingh599 visual qa computer responds to email using lstm google http googleresearch blogspot in 2015 11 computer respond to this email html lstm dramatically improves google voice search http googleresearch blogspot ch 2015 09 google voice search faster and more html another article http deeplearning net 2015 09 30 long short term memory dramatically improves google voice etc now available to a billion users understanding natural language with lstm using torch http devblogs nvidia com parallelforall understanding natural language deep neural networks using torch torch code for visual question answering using a cnn lstm model https github com abhshkdz neural vqa lstm for human activity recognition https github com guillaume chevalier lstm human activity recognition gated recurrent units gru lstm vs gru http www wildml com 2015 10 recurrent neural network tutorial part 4 implementing a grulstm rnn with python and theano time series forecasting with sequence to sequence seq2seq rnn models https github com guillaume chevalier seq2seq signal prediction a name rnn2 recursive neural network not recurrent https en wikipedia org wiki recursive neural network recursive neural tensor network rntn http deeplearning4j org recursiveneuraltensornetwork html word2vec dbn rntn for sentiment analysis http deeplearning4j org zh sentiment analysis word2vec html a name rbm restricted boltzmann machine beginner s guide about rbms http deeplearning4j org restrictedboltzmannmachine html another good tutorial http deeplearning net tutorial rbm html introduction to rbms http blog echen me 2011 07 18 introduction to restricted boltzmann machines hinton s guide to training rbms https www cs toronto edu hinton absps guidetr pdf rbms in r https github com zachmayer rbm deep belief networks tutorial http deeplearning4j org deepbeliefnetwork html word2vec dbn rntn for sentiment analysis http deeplearning4j org zh sentiment analysis word2vec html a name auto autoencoders unsupervised applies backprop after setting target input andrew ng sparse autoencoders pdf https web stanford edu class cs294a sparseautoencoder pdf deep autoencoders tutorial http deeplearning4j org deepautoencoder html denoising autoencoders http deeplearning net tutorial da html theano code http deeplearning net tutorial code da py stacked denoising autoencoders http deeplearning net tutorial sda html sda a name cnn convolutional neural networks an intuitive explanation of convolutional neural networks https ujjwalkarn me 2016 08 11 intuitive explanation convnets awesome deep vision list of resources github https github com kjw0612 awesome deep vision intro to cnns http deeplearning4j org convolutionalnets html understanding cnn for nlp http www wildml com 2015 11 understanding convolutional neural networks for nlp stanford notes http vision stanford edu teaching cs231n codes http cs231n github io github https github com cs231n cs231n github io javascript library browser based for cnns http cs stanford edu people karpathy convnetjs using cnns to detect facial keypoints http danielnouri org notes 2014 12 17 using convolutional neural nets to detect facial keypoints tutorial deep learning to classify business photos at yelp http engineeringblog yelp com 2015 10 how we use deep learning to classify business photos at yelp html interview with yann lecun kaggle http blog kaggle com 2014 12 22 convolutional nets and cifar 10 an interview with yan lecun visualising and understanding cnns https www cs nyu edu fergus papers zeilereccv2014 pdf a name nrl network representation learning awesome graph embedding https github com benedekrozemberczki awesome graph embedding awesome network embedding https github com chihming awesome network embedding network representation learning papers https github com thunlp knowledge representation learning papers https github com thunlp krlpapers graph based deep learning literature https github com naganandy graph based deep learning literature a name nlp natural language processing a curated list of speech and natural language processing resources https github com edobashira speech language processing understanding natural language with deep neural networks using torch http devblogs nvidia com parallelforall understanding natural language deep neural networks using torch tf idf explained http michaelerasm us post tf idf in 10 minutes interesting deep learning nlp projects stanford http cs224d stanford edu reports html website http cs224d stanford edu the stanford nlp group https nlp stanford edu nlp from scratch google paper https static googleusercontent com media research google com en us pubs archive 35671 pdf graph based semi supervised learning for nlp http graph ssl wdfiles com local files blog 3a start graph ssl acl12 tutorial slides final pdf bag of words https en wikipedia org wiki bag of words model classification text with bag of words http fastml com classifying text with bag of words a tutorial a name topic topic modeling topic modeling wikipedia https en wikipedia org wiki topic model probabilistic topic models princeton pdf http www cs columbia edu blei papers blei2012 pdf lda wikipedia https en wikipedia org wiki latent dirichlet allocation lsa wikipedia https en wikipedia org wiki latent semantic analysis probabilistic lsa wikipedia https en wikipedia org wiki probabilistic latent semantic analysis what is a good explanation of latent dirichlet allocation lda https www quora com what is a good explanation of latent dirichlet allocation introduction to lda http blog echen me 2011 08 22 introduction to latent dirichlet allocation another good explanation http confusedlanguagetech blogspot in 2012 07 jordan boyd graber and philip resnik html the lda buffet intuitive explanation http www matthewjockers net 2011 09 29 the lda buffet is now open or latent dirichlet allocation for english majors your guide to latent dirichlet allocation lda https medium com lettier how does lda work ill explain using emoji 108abf40fa7d difference between lsi and lda https www quora com whats the difference between latent semantic indexing lsi and latent dirichlet allocation lda original lda paper https www cs princeton edu blei papers bleingjordan2003 pdf alpha and beta in lda http datascience stackexchange com questions 199 what does the alpha and beta hyperparameters contribute to in latent dirichlet a intuitive explanation of the dirichlet distribution https www quora com what is an intuitive explanation of the dirichlet distribution topicmodels an r package for fitting topic models https cran r project org web packages topicmodels vignettes topicmodels pdf topic modeling made just simple enough https tedunderwood com 2012 04 07 topic modeling made just simple enough online lda http alexminnaar com online latent dirichlet allocation the best option for topic modeling with large data sets html online lda with spark http alexminnaar com distributed online latent dirichlet allocation with apache spark html lda in scala http alexminnaar com latent dirichlet allocation in scala part i the theory html part 2 http alexminnaar com latent dirichlet allocation in scala part ii the code html segmentation of twitter timelines via topic modeling https alexisperrier com nlp 2015 09 16 segmentation twitter timelines lda vs lsa html topic modeling of twitter followers http alexperrier github io jekyll update 2015 09 04 topic modeling of twitter followers html multilingual latent dirichlet allocation lda https github com artificiai multilingual latent dirichlet allocation lda tutorial here https github com artificiai multilingual latent dirichlet allocation lda blob master multilingual lda pipeline tutorial ipynb deep belief nets for topic modeling https github com larsmaaloee deep belief nets for topic modeling gaussian lda for topic models with word embeddings http www cs cmu edu rajarshd papers acl2015 pdf python series of lecture notes for probabilistic topic models written in ipython notebook https github com arongdari topic model lecture note implementation of various topic models in python https github com arongdari python topic model a name word2vec word2vec google word2vec https code google com archive p word2vec bag of words model wiki https en wikipedia org wiki bag of words model word2vec tutorial https rare technologies com word2vec tutorial a closer look at skip gram modeling http homepages inf ed ac uk ballison pdf lrec skipgrams pdf skip gram model tutorial http alexminnaar com word2vec tutorial part i the skip gram model html cbow model http alexminnaar com word2vec tutorial part ii the continuous bag of words model html word vectors kaggle tutorial python https www kaggle com c word2vec nlp tutorial details part 2 word vectors part 2 https www kaggle com c word2vec nlp tutorial details part 3 more fun with word vectors making sense of word2vec http rare technologies com making sense of word2vec word2vec explained on deeplearning4j http deeplearning4j org word2vec html quora word2vec https www quora com how does word2vec work other quora resources https www quora com what are the continuous bag of words and skip gram architectures in laymans terms 2 https www quora com what is the difference between the bag of words model and the continuous bag of words model 3 https www quora com is skip gram negative sampling better than cbow ns for word2vec if so why word2vec dbn rntn for sentiment analysis http deeplearning4j org zh sentiment analysis word2vec html text clustering how string clustering works http stackoverflow com questions 8196371 how clustering works especially string clustering levenshtein distance for measuring the difference between two sequences https en wikipedia org wiki levenshtein distance text clustering with levenshtein distances http stackoverflow com questions 21511801 text clustering with levenshtein distances text classification classification text with bag of words http fastml com classifying text with bag of words a tutorial named entity recognitation stanford named entity recognizer ner https nlp stanford edu software crf ner shtml named entity recognition applications and use cases towards data science https towardsdatascience com named entity recognition applications and use cases acdbf57d595e language learning with nlp and reinforcement learning http blog dennybritz com 2015 09 11 reimagining language learning with nlp and reinforcement learning kaggle tutorial bag of words and word vectors https www kaggle com c word2vec nlp tutorial details part 1 for beginners bag of words part 2 https www kaggle com c word2vec nlp tutorial details part 2 word vectors part 3 https www kaggle com c word2vec nlp tutorial details part 3 more fun with word vectors what would shakespeare say nlp tutorial https gigadom wordpress com 2015 10 02 natural language processing what would shakespeare say a closer look at skip gram modeling http homepages inf ed ac uk ballison pdf lrec skipgrams pdf a name vision computer vision awesome computer vision github https github com jbhuang0604 awesome computer vision awesome deep vision github https github com kjw0612 awesome deep vision a name svm support vector machine highest voted questions about svms on cross validated http stats stackexchange com questions tagged svm help me understand svms http stats stackexchange com questions 3947 help me understand support vector machines svm in layman s terms https www quora com what does support vector machine svm mean in laymans terms how does svm work comparisons http stats stackexchange com questions 23391 how does a support vector machine svm work a tutorial on svms http alex smola org papers 2003 smosch03b pdf practical guide to svc http www csie ntu edu tw cjlin papers guide guide pdf slides http www csie ntu edu tw cjlin talks freiburg pdf introductory overview of svms http www statsoft com textbook support vector machines comparisons svms anns http stackoverflow com questions 6699222 support vector machines better than artificial neural networks in which learn rq 1 anns svms http stackoverflow com questions 11632516 what are advantages of artificial neural networks over support vector machines another comparison http www svms org anns html trees svms http stats stackexchange com questions 57438 why is svm not so good as decision tree on the same data kernel logistic regression vs svm http stats stackexchange com questions 43996 kernel logistic regression vs svm logistic regression vs svm http stats stackexchange com questions 58684 regularized logistic regression and support vector machine 2 http stats stackexchange com questions 95340 svm v s logistic regression 3 https www quora com support vector machines what is the difference between linear svms and logistic regression optimization algorithms in support vector machines http pages cs wisc edu swright talks sjw complearning pdf variable importance from svm http stats stackexchange com questions 2179 variable importance from svm software libsvm https www csie ntu edu tw cjlin libsvm intro to svm in r http cbio ensmp fr jvert svn tutorials practical svmbasic svmbasic notes pdf kernels what are kernels in ml and svm https www quora com what are kernels in machine learning and svm intuition behind gaussian kernel in svms https www quora com support vector machines what is the intuition behind gaussian kernel in svm probabilities post svm platt s probabilistic outputs for svm http www csie ntu edu tw htlin paper doc plattprob pdf platt calibration wiki https en wikipedia org wiki platt scaling why use platts scaling http stats stackexchange com questions 5196 why use platts scaling classifier classification with platt s scaling http fastml com classifier calibration with platts scaling and isotonic regression a name rl reinforcement learning awesome reinforcement learning github https github com aikorea awesome rl rl tutorial part 1 http outlace com reinforcement learning part 1 part 2 http outlace com reinforcement learning part 2 a name dt decision trees wikipedia page lots of good info https en wikipedia org wiki decision tree learning faqs about decision trees http stats stackexchange com questions tagged cart brief tour of trees and forests https statistical research com index php 2013 04 29 a brief tour of the trees and forests tree based models in r http www statmethods net advstats cart html how decision trees work http www aihorizon com essays generalai decision trees htm weak side of decision trees http stats stackexchange com questions 1292 what is the weak side of decision trees thorough explanation and different algorithms http www ise bgu ac il faculty liorr hbchap9 pdf what is entropy and information gain in the context of building decision trees http stackoverflow com questions 1859554 what is entropy and information gain slides related to decision trees http www slideshare net pierluca lanzi machine learning and data mining 11 decision trees how do decision tree learning algorithms deal with missing values http stats stackexchange com questions 96025 how do decision tree learning algorithms deal with missing values under the hoo using surrogates to improve datasets with missing values https www salford systems com videos tutorials tips and tricks using surrogates to improve datasets with missing values good article https www mindtools com dectree html are decision trees almost always binary trees http stats stackexchange com questions 12187 are decision trees almost always binary trees pruning decision trees https en wikipedia org wiki pruning decision trees grafting of decision trees https en wikipedia org wiki grafting decision trees what is deviance in context of decision trees http stats stackexchange com questions 6581 what is deviance specifically in cart rpart discover structure behind data with decision trees http vooban com en tips articles geek stuff discover structure behind data with decision trees grow and plot a decision tree to automatically figure out hidden rules in your data comparison of different algorithms cart vs ctree http stats stackexchange com questions 12140 conditional inference trees vs traditional decision trees comparison of complexity or performance https stackoverflow com questions 9979461 different decision tree algorithms with comparison of complexity or performance chaid vs cart http stats stackexchange com questions 61230 chaid vs crt or cart cart vs chaid http www bzst com 2006 10 classification trees cart vs chaid html good article on comparison http www ftpress com articles article aspx p 2248639 seqnum 11 cart recursive partitioning wikipedia https en wikipedia org wiki recursive partitioning cart explained http documents software dell com statistics textbook classification and regression trees how to measure rank variable importance when using cart http stats stackexchange com questions 6478 how to measure rank variable importance when using cart specifically using pruning a tree in r http stackoverflow com questions 15318409 how to prune a tree in r does rpart use multivariate splits by default http stats stackexchange com questions 4356 does rpart use multivariate splits by default faqs about recursive partitioning http stats stackexchange com questions tagged rpart ctree party package in r https cran r project org web packages party party pdf show volumne in each node using ctree in r http stackoverflow com questions 13772715 show volume in each node using ctree plot in r how to extract tree structure from ctree function http stackoverflow com questions 8675664 how to extract tree structure from ctree function chaid wikipedia artice on chaid https en wikipedia org wiki chaid basic introduction to chaid https smartdrill com introduction to chaid html good tutorial on chaid http www statsoft com textbook chaid analysis mars wikipedia article on mars https en wikipedia org wiki multivariate adaptive regression splines probabilistic decision trees bayesian learning in probabilistic decision trees http www stats org uk bayesian jordan pdf probabilistic trees research paper http people stern nyu edu adamodar pdfiles papers probabilistic pdf a name rf random forest bagging awesome random forest github https github com kjw0612 awesome random forest how to tune rf parameters in practice https www kaggle com forums f 15 kaggle forum t 4092 how to tune rf parameters in practice measures of variable importance in random forests http stats stackexchange com questions 12605 measures of variable importance in random forests compare r squared from two different random forest models http stats stackexchange com questions 13869 compare r squared from two different random forest models oob estimate explained rf vs lda https stat ethz ch education semesters ss2012 ams slides v10 2 pdf evaluating random forests for survival analysis using prediction error curve https www jstatsoft org index php jss article view v050i11 why doesn t random forest handle missing values in predictors http stats stackexchange com questions 98953 why doesnt random forest handle missing values in predictors how to build random forests in r with missing na values http stackoverflow com questions 8370455 how to build random forests in r with missing na values faqs about random forest http stats stackexchange com questions tagged random forest more faqs http stackoverflow com questions tagged random forest obtaining knowledge from a random forest http stats stackexchange com questions 21152 obtaining knowledge from a random forest some questions for r implementation http stackoverflow com questions 20537186 getting predictions after rfimpute 2 http stats stackexchange com questions 81609 whether preprocessing is needed before prediction using finalmodel of randomfore 3 http stackoverflow com questions 17059432 random forest package in r shows error during prediction if there are new fact a name gbm boosting boosting for better predictions http www datasciencecentral com profiles blogs boosting algorithms for better predictions boosting wikipedia page https en wikipedia org wiki boosting machine learning introduction to boosted trees tianqi chen https homes cs washington edu tqchen pdf boostedtree pdf gradient boosting machine gradiet boosting wiki https en wikipedia org wiki gradient boosting guidelines for gbm parameters in r http stats stackexchange com questions 25748 what are some useful guidelines for gbm parameters strategy to set parameters http stats stackexchange com questions 35984 strategy to set the gbm parameters meaning of interaction depth http stats stackexchange com questions 16501 what does interaction depth mean in gbm 2 http stats stackexchange com questions 16501 what does interaction depth mean in gbm role of n minobsinnode parameter of gbm in r http stats stackexchange com questions 30645 role of n minobsinnode parameter of gbm in r gbm in r http www slideshare net mark landry gbm package in r faqs about gbm http stats stackexchange com tags gbm hot gbm vs xgboost https www kaggle com c higgs boson forums t 9497 r s gbm vs python s xgboost xgboost xgboost tuning kaggle https www kaggle com khozzy rossmann store sales xgboost parameter tuning template log xgboost vs gbm https www kaggle com c otto group product classification challenge forums t 13012 question to experienced kagglers and anyone who wants to take a shot 68296 post68296 xgboost survey https www kaggle com c higgs boson forums t 10335 xgboost post competition survey practical xgboost in python online course free http education parrotprediction teachable com courses practical xgboost in python adaboost adaboost wiki https en wikipedia org wiki adaboost python code https gist github com tristanwietsma 5486024 adaboost sparse input support http hamzehal blogspot com 2014 06 adaboost sparse input support html adabag r package https cran r project org web packages adabag adabag pdf tutorial http math mit edu rothvoss 18 304 3pm presentations 1 eric boosting304finalrpdf pdf catboost catboost documentation https catboost ai docs benchmarks https catboost ai benchmark tutorial https github com catboost tutorials github project https github com catboost catboost vs light gbm vs xgboost https towardsdatascience com catboost vs light gbm vs xgboost 5f93620723db a name ensem ensembles wikipedia article on ensemble learning https en wikipedia org wiki ensemble learning kaggle ensembling guide http mlwave com kaggle ensembling guide the power of simple ensembles http www overkillanalytics net more is always better the power of simple ensembles ensemble learning intro http machine learning martinsewell com ensembles ensemble learning paper http cs nju edu cn zhouzh zhouzh files publication springerebr09 pdf ensembling models with r http amunategui github io blending models ensembling regression models in r http stats stackexchange com questions 26790 ensembling regression models intro to ensembles in r http www vikparuchuri com blog intro to ensemble learning in r ensembling models with caret http stats stackexchange com questions 27361 stacking ensembling models with caret bagging vs boosting vs stacking http stats stackexchange com questions 18891 bagging boosting and stacking in machine learning good resources kaggle africa soil property prediction https www kaggle com c afsis soil properties forums t 10391 best ensemble references boosting vs bagging http www chioka in which is better boosting or bagging resources for learning how to implement ensemble methods http stats stackexchange com questions 32703 resources for learning how to implement ensemble methods how are classifications merged in an ensemble classifier http stats stackexchange com questions 21502 how are classifications merged in an ensemble classifier a name stack stacking models stacking blending and stacked generalization http www chioka in stacking blending and stacked generalization stacked generalization stacking http machine learning martinsewell com ensembles stacking stacked generalization when does it work http www ijcai org proceedings 97 2 011 pdf stacked generalization paper http citeseerx ist psu edu viewdoc download doi 10 1 1 56 1533 rep rep1 type pdf a name vc vapnik chervonenkis dimension wikipedia article on vc dimension https en wikipedia org wiki vc dimension intuitive explanantion of vc dimension https www quora com explain vc dimension and shattering in lucid way video explaining vc dimension https www youtube com watch v pudzy2xmr5c introduction to vc dimension http www svms org vc dimension faqs about vc dimension http stats stackexchange com questions tagged vc dimension do ensemble techniques increase vc dimension http stats stackexchange com questions 78076 do ensemble techniques increase vc dimension a name bayes bayesian machine learning bayesian methods for hackers using pymc https github com camdavidsonpilon probabilistic programming and bayesian methods for hackers should all machine learning be bayesian http videolectures net bark08 ghahramani samlbb tutorial on bayesian optimisation for machine learning http www iro umontreal ca bengioy cifar ncap2014 summerschool slides ryan adams 140814 bayesopt ncap pdf bayesian reasoning and deep learning http blog shakirm com 2015 10 bayesian reasoning and deep learning slides http blog shakirm com wp content uploads 2015 10 bayes deep pdf bayesian statistics made simple http greenteapress com wp think bayes kalman bayesian filters in python https github com rlabbe kalman and bayesian filters in python markov chain wikipedia page https en wikipedia org wiki markov chain a name semi semi supervised learning wikipedia article on semi supervised learning https en wikipedia org wiki semi supervised learning tutorial on semi supervised learning http pages cs wisc edu jerryzhu pub sslicml07 pdf graph based semi supervised learning for nlp http graph ssl wdfiles com local files blog 3a start graph ssl acl12 tutorial slides final pdf taxonomy http is tuebingen mpg de fileadmin user upload files publications taxo 0 pdf video tutorial weka https www youtube com watch v swxcijzfgnm unsupervised supervised and semi supervised learning http stats stackexchange com questions 517 unsupervised supervised and semi supervised learning research papers 1 http mlg eng cam ac uk zoubin papers zglactive pdf 2 http mlg eng cam ac uk zoubin papers zgl pdf 3 http icml cc 2012 papers 616 pdf a name opt optimization mean variance portfolio optimization with r and quadratic programming http www wdiam com 2012 06 10 mean variance portfolio optimization with r and quadratic programming utm content buffer04c12 utm medium social utm source linkedin com utm campaign buffer algorithms for sparse optimization and machine learning http www ima umn edu 2011 2012 w3 26 30 12 activities wright steve sjw ima12 optimization algorithms in machine learning http pages cs wisc edu swright nips2010 sjw nips10 pdf video lecture http videolectures net nips2010 wright oaml optimization algorithms for data analysis http www birs ca workshops 2011 11w2035 files wright pdf video lectures on optimization http videolectures net stephen j wright optimization algorithms in support vector machines http pages cs wisc edu swright talks sjw complearning pdf the interplay of optimization and machine learning research http jmlr org papers volume7 mlopt intro06a mlopt intro06a pdf hyperopt tutorial for optimizing neural networks hyperparameters http vooban com en tips articles geek stuff hyperopt tutorial for optimizing neural networks hyperparameters a name other other tutorials for a collection of data science tutorials using r please refer to this list https github com ujjwalkarn datasciencer for a collection of data science tutorials using python please refer to this list https github com ujjwalkarn datasciencepython | deep-learning-tutorial machine-learning machinelearning deeplearning neural-network neural-networks deep-neural-networks awesome-list awesome list deep-learning | ai |
iotex-core | go version https img shields io badge go 1 9 2 blue svg https github com moovweb gvm circleci https circleci com gh iotexproject iotex core svg style svg circle token fe0817d127f251a34b8bdd3336a808c7537e5ec0 https circleci com gh iotexproject iotex core iotex core welcome to the official go implementation of iotex protocol iotex is building the next generation of the decentralized network for iot powered by scalability and privacy centric blockchains please refer to iotex whitepaper https iotex io white paper for details currently this repo is of alpha quality with limited features supported and it is subjected to rapid change please contact us if you intend to run it in production system components and flowchart systemflowchart https user images githubusercontent com 15241597 38832065 3e57ca3a 4176 11e8 9bff 110387cf2378 png feature list testnet preview codename stonevan 1 tbc transactions block chain bech32 encoded address serialization and deserialize of messages on the wire merkle tree transactions blocks and chain transaction pool fast and reliable blockchain storage and query using boltdb block sync from network peers basic framework for script and vm 2 network efficient gossip protocol over tls broadcast unicast semantics seeding through network config rate limit requests per connection peer discovery large scale simulation and load test 3 consensus framework for plugable consensus standalone and noop schemes basic implementation of r dpos scheme 4 clients initial rpc support tools for injecting transactions blocks 5 testing integration unit test coverage 50 integration tests staging development to 50 nodes for internal use only testnet alpha beta libsect283k1 and integration random beacon and full r dpos with voting support lightweight stealth address cross chain communication ccc fast block sync and checkpointing script and vm full explorer and wallet supporting hierarchical deterministic hd addresses spv clients seeding through ipfs and version negotiation pluggable transportation framework w udp tcp support peer metrics unit test coverage 70 e2e demo among 500 1000 peers enhancement of existing features and much more dev tips minimum requirements components version description golang https golang org 1 9 2 the go programming language glide https github com masterminds glide 0 13 0 glide is a dependency management tool for go setup dev environment mkdir p go src github com iotexproject cd go src github com iotexproject git clone git github com iotexproject iotex core git cd iotex core glide install make fmt make build setup precommit hook install git hook tools from precommit hook https pre commit com first and then pre commit install run unit tests make test run make run you will see log message output like w0416 12 52 15 652394 1576 blocksync go 220 receive tip block 116 w0416 12 52 15 653014 1576 blocksync go 276 127 0 0 1 4689 receive block 116 in 616 939 s w0416 12 52 15 653967 1576 blocksync go 293 commit block 116 time 923 364 s w0416 12 52 16 648667 1576 blocksync go 276 127 0 0 1 4689 receive block 117 in 994 656929ms w0416 12 52 16 649745 1576 blocksync go 293 commit block 117 time 1 029462ms w0416 12 52 17 648360 1576 blocksync go 276 127 0 0 1 4689 receive block 118 in 998 560518ms w0416 12 52 17 649604 1576 blocksync go 293 commit block 118 time 1 186833ms w0416 12 52 18 648309 1576 blocksync go 276 127 0 0 1 4689 receive block 119 in 998 658293ms w0416 12 52 18 649432 1576 blocksync go 293 commit block 119 time 1 075772ms w0416 12 52 19 653393 1576 blocksync go 276 127 0 0 1 4689 receive block 120 in 1 003920977s w0416 12 52 19 654698 1576 blocksync go 293 commit block 120 time 1 256924ms w0416 12 52 20 649165 1576 blocksync go 276 127 0 0 1 4689 receive block 121 in 994 424355ms w0416 12 52 20 650254 1576 blocksync go 293 commit block 121 time 1 0282ms w0416 12 52 21 653420 1576 blocksync go 276 127 0 0 1 4689 receive block 122 in 1 00312559s w0416 12 52 21 654650 1576 blocksync go 293 commit block 122 time 1 182673ms deploy w docker image docker build t stonevan docker run stonevan contribution we are glad to have contributors out of the core team contributions including but not limited to style bug fixes implementation of features proposals of schemes algorithms and thorough documentation are welcomed please refer to our contribution guideline https github com iotexproject iotex core blob master contributing md for more information license this project is licensed under the apache license 2 0 https github com iotexproject iotex core blob master license md | server |
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CS179J | cs179j welcome to my repository for my embedded systems senior design porject this project utilizes the raspberry pi 2b as the main hardware and python as the main programming language i built a portable and merciful pest control device that is used for catching pests asthey wander into it it can notify the user via text and email when it has captured something as well as takes a picture and sends that as well the user can also use a live feed by using a camera app for the raspberry pi for more info feel free to read the write up in my repository | os |
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Create-BlockchainNetwork-IBPV20 | build status https travis ci org ibm create blockchainnetwork ibpv20 svg branch master https travis ci org ibm create blockchainnetwork ibpv20 create blockchainnetwork ibpv20 creating a basic blockchain network using the ibm blockchain platform welcome to the first in a series of building a blockchain application using the ibm blockchain platform part 1 will show you how to set up your blockchain network on the ibm cloud this will be the hello world of hyperledger samples using the ibm blockchain platform so beginner developers should be able to manage this this pattern shows you how to test your network by packaging your smart contract using the ibm blockchain platform extension on vs code and then deploying it onto the network the network uses hyperledger fabric v1 4 hyperledger fabric is a blockchain framework implementation and one of the hyperledger projects hosted by the linux foundation intended as a foundation for developing applications or solutions with a modular architecture hyperledger fabric allows components such as consensus and membership services to be plug and play in part 2 https github com ibm smartcontracttrading wfabric1 4 vscodeext we will explore more about creating a complex network with multiple participants and using access control rules acl to provide them network access permissions in this journey you will run hyperledger fabric on the cloud when you have completed this code pattern you will understand how to package the smart contract using ibm blockchain platform extension for vs code setup a hyperledger fabric network on ibm blockchain platform install and instantiate smart contract package onto the ibm blockchain platform interact with the contract and execute transactions using the sdk architecture flow p align center img src https user images githubusercontent com 8854447 72624131 5cf65c80 3914 11ea 85cf 53806a073433 png p 1 the developer develops a smart contract using node js 2 use the ibm blockchain platform extension for vs code to package the smart contract 3 setup and launch the ibm blockchain platform service 4 the ibm blockchain platform enables the creation of a network onto a ibm cloud kubernetes service enabling installation and instantiation of the smart contract on the network 5 the node js application uses the fabic sdk to interact with the deployed network on ibm blockchain platform and issues transactions included components ibm blockchain platform https www ibm com cloud blockchain platform gives you total control of your blockchain network with a user interface that can simplify and accelerate your journey to deploy and manage blockchain components on the ibm cloud kubernetes service ibm cloud kubernetes service https www ibm com cloud container service creates a cluster of compute hosts and deploys highly available containers a kubernetes cluster lets you securely manage the resources that you need to quickly deploy update and scale applications ibm blockchain platform extension for vs code https marketplace visualstudio com items itemname ibmblockchain ibm blockchain platform is designed to assist users in developing testing and deploying smart contracts including connecting to hyperledger fabric environments featured technologies hyperledger fabric v1 4 https hyperledger fabric readthedocs io is a platform for distributed ledger solutions underpinned by a modular architecture that delivers high degrees of confidentiality resiliency flexibility and scalability node js https nodejs org en is an open source cross platform javascript run time environment that executes server side javascript code prerequisites ibm cloud account https cloud ibm com registration target 2fdashboard 2fapps node v8 x or v10 x and npm v6 x or greater https nodejs org en download vscode version 1 38 0 or greater https code visualstudio com ibm blockchain platform extension for vscode https marketplace visualstudio com items itemname ibmblockchain ibm blockchain platform running the application follow these steps to set up and run this code pattern the steps are described in detail below steps 1 clone the repo 1 clone the repo 2 package the smart contract 2 package the smart contract 3 create ibm cloud services 3 create ibm cloud services 4 build a network 4 build a network 5 deploy blockchain network smart contract on the network 5 deploy blockchain network smart contract on the network 6 connect application to the network 6 connect application to the network 7 run the application 7 run the application 1 clone the repo clone this repository in a folder your choice git clone https github com ibm create blockchainnetwork ibpv20 2 package the smart contract we will use the ibm blockchain platform extension on vs code to package the smart contract if you have not done so already you will need to install the ibm blockchain platform vscode extension you ll also need to install the latest version of vscode to do this to see if you have the latest version go to help check for updates if vscode exits at this point it likely means you don t have the latest version if so update your vscode using the link provided earlier and once you re done click on extensions in the sidebar on the left side of your screen at the top search the extensions marketplace for ibm blockchain platform and click on install you should see a status of installing and eventually installed then click on reload open visual studio code and open the contract folder from create blockchainnetwork repository that was cloned earlier it is important that you are opening the contract folder and not the entire create blockchainnetwork directory otherwise you will see an error that states that it doesn t understand what programming language you are using press the f1 key to see the different vs code options choose ibm blockchain platform package open project p align center img src https user images githubusercontent com 8854447 71910509 05036d00 3140 11ea 8b15 7c8aeb403974 png p click the ibm blockchain platform extension button on the left this will show the packaged contracts on top and the blockchain connections on the bottom p align center img height 500 src https user images githubusercontent com 8854447 72625681 38e84a80 3917 11ea 8bd1 88d78a1dc99e png p next right click on the packaged contract in this case select blockchain network 0 0 1 to export it and choose export package choose a location on your machine and save the cds file we will use this packaged smart contract later to deploy on the ibm blockchain platform service now we will start setting up the different services required for configuring our hyperledger fabric network on the ibm cloud and for running our application using this network 3 create ibm cloud services create the ibm cloud kubernetes service https cloud ibm com kubernetes catalog cluster you can find the service in the catalog for this code pattern we can use the free cluster and give it a name note that the ibm cloud allows one instance of a free cluster which expires after 30 days note it could take 20 minutes for the ibm cloud kubernetes service setup to complete br p align center img src https user images githubusercontent com 8854447 71910506 046ad680 3140 11ea 9f4b 8bcb4d2a651b gif p br create the ibm blockchain platform https cloud ibm com catalog services blockchain platform service on the ibm cloud you can find the service in the catalog and give it a name br p align center img src https user images githubusercontent com 8854447 71910502 046ad680 3140 11ea 9853 3598b9363d91 gif p br after your kubernetes cluster is up and running you can deploy your ibm blockchain platform on the cluster again wait for the ibm cloud kubernetes service to indicate it was deployed the ibm blockchain platform service walks through few steps and finds your cluster on the ibm cloud to deploy the service on br p align center img src https user images githubusercontent com 8854447 71910501 046ad680 3140 11ea 8440 9d2fef0be426 gif p br once the blockchain platform is deployed on the kubernetes cluster you can launch the console to start configuring your blockchain network 4 build a network we will build a network as provided by the ibm blockchain platform documentation https cloud ibm com docs services blockchain howto topic blockchain ibp console build network ibp console build network this will include creating a channel with a single peer organization with its own msp and ca certificate authority and an orderer organization with its own msp and ca we will create the respective identities to deploy peers and operate nodes create your peer organization ca navigate to the b nodes b tab in the left navigation and click b add certificate authority b click b create an ibm cloud certificate authority b and b next b give it a b ca display name b of org1 ca and click b next b specify an b ca administrator enroll id b of admin and b ca administrator enroll secret b of adminpw then click b next b review the summary and click b add certificate authority b br p align center img src https user images githubusercontent com 8854447 71913565 bb1d8580 3145 11ea 9eaa 1b4e8a10e985 gif p br associate the peer organization ca admin identity in the nodes tab select the b org1 ca b once it is running indicated by the green box in the tile click b associate identity b on the ca overview panel on the side panel select b enroll id b provide an b enroll id b of admin and an b enroll secret b of adminpw use the default value of org1 ca identity for the b identity display name b click b associate identity b to add the identity into your wallet and associate the admin identity with the b org1 ca b br p align center img src https user images githubusercontent com 8854447 71913744 1e0f1c80 3146 11ea 85e4 eea5280aa8e9 gif p br use peer organization ca to register the peer and org1 admin identities select the b org1 ca b certificate authority and ensure the admin identity that was created for the ca is visible in the table we will register an admin for our organization org1 click on the b register user b button give an b enroll id b of org1admin and b enroll secret b of org1adminpw set the b type b for this identity as client we can specify to b use root affiliation b or uncheck this field and select from any of the affiliated organizations from the drop down list we will leave the b maximum enrollments b field blank click b next b we will not be adding any attributes to this user click b register user b we will repeat the process to create an identity of the peer click on the b register user b button give an b enroll id b of peer1 and b enroll secret b of peer1pw set the b type b for this identity as peer we can specify to b use root affiliation b or uncheck this field and select from any of the affiliated organizations from the drop down list click b next b we will not be adding any attributes to this user click b register user b br p align center img src https user images githubusercontent com 8854447 71913929 7c3bff80 3146 11ea 9930 a455f1e45fe2 gif p br create the peer organization msp definition navigate to the b organizations b tab in the left navigation and click b create msp definition b enter the b msp display name b as org1msp and an b msp id b of org1msp under b root certificate authority b details specify the peer ca that we created org1 ca as the root ca for the organization give the b enroll id b and b enroll secret b for your organization admin org1admin and org1adminpw then give the identity name as org1 admin click the b generate b button to enroll this identity as the admin of your organization and export the identity to the wallet click b export b to export the admin certificates to your file system finally click b create msp definition b br p align center img src https user images githubusercontent com 8854447 71914115 e5bc0e00 3146 11ea 891c 6422bc4c2c4e gif p br create a peer navigate to the b nodes b tab in the left navigation and click b add peer b click b create an ibm cloud peer b and then click b next b give the b peer display name b as peer org1 and click b next b on the next screen select org1 ca as the b certificate authority b then give the b peer enroll id b and b peer enroll secret b for the peer identity that you created for your peer that is peer1 and peer1pw select the b organization msp b as org1msp from the drop down list leave the b tls csr hostname b blank click b next b the next step is to associate an identity with this peer to make it the admin of your peer select your peer admin identity org1 admin and click b next b review the summary and click b add peer b br p align center img src https user images githubusercontent com 8854447 71914297 53683a00 3147 11ea 9ecb bace14e5e5c5 gif p br create your orderer organization ca navigate to the b nodes b tab in the left navigation and click b add certificate authority b click b create an ibm cloud certificate authority b and b next b give it a b ca display name b of orderer ca and click b next b specify an b ca administrator enroll id b of admin and b ca administrator enroll secret b of adminpw then click b next b review the summary and click b add certificate authority b br p align center img src https user images githubusercontent com 8854447 71914392 86123280 3147 11ea 9a6f b6eddab790b1 gif p br associate the orderer organization ca admin identity in the nodes tab select the b orderer ca b once it is running indicated by the green box in the tile click b associate identity b on the ca overview panel on the side panel select b enroll id b provide an b enroll id b of admin and an b enroll secret b of adminpw use the default value of orderer ca identity for the b identity display name b click b associate identity b to add the identity into your wallet and associate the admin identity with the b orderer ca b br p align center img src https user images githubusercontent com 8854447 71914593 e73a0600 3147 11ea 8944 1c5e2bbecfba gif p br use orderer organization ca to register orderer and orderer admin identities select the b orderer ca b certificate authority and ensure the admin identity that was created for the ca is visible in the table we will register an admin for the orderer organization click on the b register user b button give an b enroll id b of ordereradmin and b enroll secret b of ordereradminpw set the b type b for this identity as client we can specify to b use root affiliation b or uncheck this field and select from any of the affiliated organizations from the drop down list we will leave the b maximum enrollments b field blank click b next b we will not be adding any attributes to this user click b register user b we will repeat the process to create an identity of the orderer click on the b register user b button give an b enroll id b of orderer1 and b enroll secret b of orderer1pw set the b type b for this identity as orderer we can specify to b use root affiliation b or uncheck this field and select from any of the affiliated organizations from the drop down list click b next b we will not be adding any attributes to this user click b register user b br p align center img src https user images githubusercontent com 8854447 71914721 35e7a000 3148 11ea 8db6 2d3584fca238 gif p br create the orderer organization msp definition navigate to the b organizations b tab in the left navigation and click b create msp definition b enter the b msp display name b as orderermsp and an b msp id b of orderermsp under b root certificate authority b details specify the peer ca that we created orderer ca as the root ca for the organization give the b enroll id b and b enroll secret b for your organization admin ordereradmin and ordereradminpw then give the identity name as orderer admin click the b generate b button to enroll this identity as the admin of your organization and export the identity to the wallet click b export b to export the admin certificates to your file system finally click b create msp definition b br p align center img src https user images githubusercontent com 8854447 71914893 95de4680 3148 11ea 8a9d 5952c26c8cdc gif p br create an orderer navigate to the b nodes b tab in the left navigation and click b add ordering service b click b create an ibm cloud ordering service b and then click b next b give the b ordering service display name b as orderer and click b next b on the next screen select orderer ca as the b certificate authority b then give the b ordering service enroll id b and b ordering service enroll secret b for the peer identity that you created for your orderer that is orderer1 and orderer1pw select the b organization msp b as orderermsp from the drop down list leave the b tls csr hostname b blank click b next b the next step is to associate an identity with this peer to make it the admin of your peer select your peer admin identity orderer admin and click b next b review the summary and click b add ordering service b br p align center img src https user images githubusercontent com 8854447 71915205 42b8c380 3149 11ea 8050 5edfd461ae10 gif p br add organization as consortium member on the orderer to transact navigate to the b nodes b tab and click on the b orderer b that we created under b consortium members b click b add organization b from the drop down list select org1msp as this is the msp that represents the peer s organization org1 click b add organization b br p align center img src https user images githubusercontent com 8854447 71915342 88758c00 3149 11ea 98e2 2ed00dc9c8c3 gif p br create the channel navigate to the b channels b tab in the left navigation and click b create channel b give the b channel name b as mychannel select the orderer you created orderer from the b ordering service b drop down list under b organizations b select org1msp org1msp from the drop down list to add the organization org1 as a member of this channel click b add b button set the permissions for this member as b operator b scroll down to the b channel creator organization b section and select org1msp org1msp from the dropdown as the b channel creator msp b and select org1 admin from the dropdown under b identity b click b create channel b br p align center img src https user images githubusercontent com 8854447 71915595 15b8e080 314a 11ea 9843 d7df9be30fe5 gif p br join your peer to the channel click b join channel b to add a peer to the channel select your orderer as the b ordering service b and click b next b enter the name of the b channel b as mychannel and click b next b next we need to select which peers should be added to the channel in our case we just want to add the peer we created under org1 select peer org1 click b join channel b br p align center img src https user images githubusercontent com 8854447 71915747 67fa0180 314a 11ea 984b 80deb0877d03 gif p br 5 deploy blockchain network smart contract on the network install a smart contract navigate to the b smart contracts b tab in the left navigation and click b install smart contract b browse to the location of the blockchain network smart contract package file it is probably named blockchain network 0 0 1 cds which we packaged earlier using the ibm blockchain platform extension for visual studio code click on b add file b and find your packaged smart contract once the contract is uploaded click b install smart contract b br p align center img src https user images githubusercontent com 8854447 72628313 0bea6680 391c 11ea 93c7 ccb59ff94525 gif p br instantiate smart contract under b installed smart contracts b find the smart contract from the list note ours is called blockchain network installed on our peer and click b instantiate b from the overflow menu on the right side of the row on the side panel that opens select the channel mychannel on which to instantiate the smart contract click b next b select the organization members to be included in the endorsement policy in our case we need to select org1msp click b next b we can skip the b setup private data collection b step and simply click b next b give the b function name b of instantiate and leave b arguments b blank note instantiate is the method in the my contract js contract file that initiates the smart contracts on the peer some may name this initledger click b instantiate b br p align center img src https user images githubusercontent com 8854447 72628995 72bc4f80 391d 11ea 8891 db04e4ca142a gif p br 6 connect application to the network connect with sdk through connection profile scroll down to the b instantiated smart contracts b section and find the blockchain network contract in the list click on connect with sdk from the overflow menu on the right side of the row from the dropdown for b msp for connection b choose org1msp from the dropdown for b certificate authority b choose org1 ca download the connection profile by scrolling down and clicking b download connection profile b this will download the connection json which we will use to establish a connection between the node js web application and the blockchain network you can click b close b once the download completes br p align center img src https user images githubusercontent com 8854447 72628868 38eb4900 391d 11ea 8d65 00fd6f416bca gif p br create an application admin navigate to the b nodes b tab in the left navigation and under b certificate authorities b choose your organization ca b org1 ca b click on b register user b give an b enroll id b of app admin and b enroll secret b of app adminpw set the b type b for this identity as client we can specify to b use root affiliation b or uncheck this field and select from any of the affiliated organizations from the drop down list we will leave the b maximum enrollments b field blank click b next b under b attributes b click on b add attribute b give attribute as hf registrar roles this will allow this identity to act as a registrar and issue identities for our app click b add attribute b click b register user b br p align center img src https user images githubusercontent com 8854447 72450922 25a77480 3789 11ea 9ce3 2319e7e11008 gif p br update application connection copy the connection profile you downloaded into the application folder application update the config json application config json file with the connection json file name you downloaded the b enroll id b and b enroll secret b for your app admin which we earlier provided as app admin and app adminpw the orgmsp id which we provided as org1msp the caname which can be found in your connection json file under organization org1msp certificateauthorities this would be like an ip address and a port the username you would like to register update gateway discovery to enabled true aslocalhost false to connect to ibm blockchain platform bash connection file mychannel blockchain network profile json channel name mychannel smart contract name blockchain network appadmin app admin appadminsecret app adminpw orgmspid org1msp caname 169 46 208 151 30404 username user1 gatewaydiscovery enabled true aslocalhost false 7 run the application enroll admin first navigate to the application directory and install the node dependencies bash cd application npm install run the enrolladmin js script bash node enrolladmin js you should see the following in the terminal bash msg successfully enrolled admin user app admin and imported it into the wallet run the invoke transactions js script to execute the transactions on the smart contract bash node invoke transactions js you should see the following in the terminal bash wallet path users snyk cognitiveapps code patterns create blockchainnetwork ibpv20 create blockchainnetwork ibpv20 application wallet submit addtrader transaction addtraderaresponse traderid tradera firstname carlos lastname roca addtraderaresponse json parse traderid tradera firstname carlos lastname roca submit addtrader transaction addtraderbresponse traderid traderb firstname lisa lastname smith addtraderbresponse json parse traderid traderb firstname lisa lastname smith submit addcommodity transaction addcommodityresponse tradingsymbol commoditya description farm commodity traderid tradera addcommodityresponse json parse tradingsymbol commoditya description farm commodity traderid tradera submit commodity trade transaction commoditytraderesponse description farm commodity traderid traderb tradingsymbol commoditya commoditytraderesponse json parse description farm commodity traderid traderb tradingsymbol commoditya troubleshooting if you receive the following error on submitting transaction error client js channel not found for name mychannel it is safe to ignore this error because the ibm blockchain platform service has service discovery enabled by default in order to use service discovery to find other peers please define anchor peers for your channel in the ui if you really want the message to go away you can add the channels section to the connection profile but it is a warning rather than a true error telling the user the channel is found but not in the connection profile as an example you can manually add the following json and update the ip address and ports manually channels mychannel orderers 169 46 208 151 32078 peers 169 46 208 151 31017 extending the code pattern this application can be expanded in a couple of ways create a wallet for every member and use the member s wallet to interact with the application add a ui application in place of the invoke js node application to execute the transactions links hyperledger fabric docs http hyperledger fabric readthedocs io en latest zero to blockchain https www redbooks ibm com redbooks nsf redbookabstracts crse0401 html open ibm code patterns for blockchain https developer ibm com patterns category blockchain 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 https www apache org licenses license 2 0 txt apache software license asl faq https www apache org foundation license faq html whatdoesitmean | blockchain vscode-extension hyperledger-fabric | blockchain |
azure-iot-explorer | azure iot explorer preview ci pipeline build status https dev azure com azure azure iot explorer apis build status azure 20iot 20explorer 20ci 20pipeline branchname main https dev azure com azure azure iot explorer build latest definitionid 31 branchname main release pipeline build status https dev azure com azureiotdevxp azure iot explorer apis build status official prod 20 20release 20 20azure 20iot 20explorer branchname main https dev azure com azureiotdevxp azure iot explorer build latest definitionid 95 branchname main table of contents getting azure iot explorer getting azure iot explorer features features contributing contributing getting azure iot explorer you can either download a pre built version or build it yourself download a pre built version go to the releases https github com azure azure iot explorer releases tab download the installer corresponding to your platform and install run it locally and build it yourself 1 open a node capable command prompt 1 clone the repo git clone https github com azure azure iot explorer git 1 run npm install 1 run npm start a new tab in your default browser will be opened automatically pointing to the locally running site 1 optional stop step 4 then run npm run build and then run npm run electron the electron app will spin up using the bits generated in the dist folder if you d like to package the app yourself please refer to the faq https github com azure azure iot explorer wiki faq features configure an iot hub connection upon opening the application choose an authentication method and connect to an azure iot hub if you picked connect via iot hub connection string you can add multiple strings view update or delete them anytime by returning to home if you picked connect via azure active directory you will be redirected to login in through aad from where you will be able to pick a subscription and then pick an iot hub you can switch back and forth between these two authentication methods img src doc screenrecords login gif alt login width 800 device crud click new to create a new device select device s and click delete to delete device s multiple devices can be selected by clicking while dragging the mouse devices can by queried by typing the first few characters of a device name in the query box img src doc screenrecords create device gif alt create device width 800 device functionalities click on the device name to see the device details and interact with the device check out the list of features that we support https github com azure azure iot explorer wiki img src doc screenrecords device features gif alt device details width 800 plug and play if you are looking for a ui tool to get a flavor of plug and play look no futher follow this microsoft docs https docs microsoft com en us azure iot pnp overview iot plug and play to get started once your device has gone through discovery iot plug and play components page would be available on device details view the model id would be shown follow our guidance to set up how we can retrieve model definitions if it is already setup we will inform you where are we resolving your model definitions from a table would show the list of components implemented by the device and the corresponding interfaces the components conform to you can go back to home either from device or by directly clicking the breadcrumb to change how we resolve model definitions note this is a global setting which would affect across the hub img src doc screenrecords pnp discovery gif alt pnp discovery width 800 click the name of any component and switch between interface properties commands and telemetry to start interacting with the pnp device img src doc screenrecords pnp interaction property gif alt pnp interaction property width 800 img src doc screenrecords pnp interaction telemetry gif alt pnp interaction telemetry width 800 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 | azure-iot devices plugandplay pnp iot azure iothub iothub-platform dtdl dtdl-models | server |
LLM-QAT | llm qat this repository contains the training code of llm qat introduced in our work llm qat data free quantization aware training for large language models https arxiv org abs 2305 17888 in this work we investigate quantization aware training for llms llm qat in addition to quantizing weights and activations we also quantize the kv cache which is critical for increasing throughput and support long sequence dependencies at current model sizes we experiment with llama models of sizes 7b 13b and 30b at quantization levels down to 4 bits we observe up to 20 points improvement over training free methods when quantizing weight activations and kv cache to 4 bit 8 bit and 4 bit respectively div align center img width 80 src llm qat overview jpg div citation if you find our code useful for your research please consider citing article liu2023llm title llm qat data free quantization aware training for large language models author liu zechun and oguz barlas and zhao changsheng and chang ernie and stock pierre and mehdad yashar and shi yangyang and krishnamoorthi raghuraman and chandra vikas journal arxiv preprint arxiv 2305 17888 year 2023 run 1 requirements python 3 9 pytorch 1 13 pip install r requirement txt install apex from source https github com nvidia apex 2 steps to run 1 synthesize data download the llama 7b model from huggingface https huggingface co decapoda research llama 7b hf find it in the huggingface cache and update the path in generate data py run python generate data py i here i is the gpu id ranging from 0 to 63 because we use 64 gpus to synthesize data in parallel you can also change n vocab in your code to adjust the degree of parallelism run python merge gen data py to merge all the generated data in one jsonl file 2 quantization aware training specify the data path and the pre trained model path in scrips run sh file run bash run train sh w bit a bit kv bit e g bash run train sh 4 8 4 for 4 bit weight 8 bit activation and 4 bit kv cache quantized llama 7b models the results reported in the paper is run with the internal llama codebase in meta we reproduced our experiments with huggingface codebase and released code here the results are close to those in the paper for clearity we list the zero shot common sense reasoning accuracy of the opensourced version in the following table bits w a kv boolq piqa siqa hellaswag winogrande arc easy arc challenge obqa avg 4 8 4 72 4 76 9 47 6 70 5 65 8 67 5 44 4 50 4 62 0 4 8 8 73 6 77 4 48 5 73 0 68 8 68 4 45 5 53 4 63 6 4 6 16 70 8 76 0 46 9 70 9 65 2 66 7 43 5 49 0 61 1 4 8 16 72 9 77 9 47 9 72 9 68 0 69 1 44 8 55 6 63 6 4 16 16 74 2 78 2 48 3 73 3 68 2 69 7 45 6 54 8 64 0 8 8 4 74 1 78 6 49 3 73 3 67 9 70 1 45 5 52 4 63 9 8 8 8 75 5 79 1 48 7 75 5 70 1 73 1 47 2 56 0 65 6 8 8 16 75 7 79 1 48 9 75 8 70 4 72 8 47 8 56 3 65 9 acknowledgement this code is partially based on huggingface transformer repo contact zechun liu reality labs meta inc zechunliu at meta dot com barlas oguz meta ai barlaso at meta dot com changsheng zhao reality labs meta inc cszhao at meta dot com license bit is cc by nc 4 0 licensed as of now | ai |
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Final-Exam-Project | final exam project altschool cloud engineering final exam | cloud |
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