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Zef | zef computer vision library | ai |
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FlutterIOT | flutteriot the simple iot project using flutter google assistant screenshot p align center img src https github com brinesoftwares flutteriot blob master screenshots app screenshot jpeg raw true width 350 title hover text p circuit p align center img src https github com brinesoftwares flutteriot blob master screenshots led circuit jpg raw true width 350 title hover text p language used flutter arduino backend firebase google assistant hardware nodemcu esp8266 led | flutter iot-application iot ml google-asistant embedded-systems nodemcu-arduino android-application ios-app | server |
bert_brain_neurips_2019 | bert brain code for using bert model to predict brain activity data | ai |
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Embedded-Design---Pan-Da-Grey-Wolf | embedded design pan da grey wolf my embedded system design project game rules jpg start page jpg | os |
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programming-book | programming book go to the project pages https evanli github io programming book to see the books programming book series programming book https github com evanli programming book algorithm https github com evanli programming book algorithm back end https github com evanli programming book back end database https github com evanli programming book database front end https github com evanli programming book front end git https github com evanli programming book git programming book 2 https github com evanli programming book 2 c https github com evanli programming book 2 c go https github com evanli programming book 2 go javascript https github com evanli programming book 2 javascript node js https github com evanli programming book 2 nodejs programming book 3 https github com evanli programming book 3 python https github com evanli programming book 3 python machine learning https github com evanli programming book 3 machine learning deep learning https github com 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github com evanli programming book raw master front end html5 pdf html5 web front end html5 web pdf download 42 16m https github com evanli programming book raw master front end html5 web pdf react front end react pdf download 19 30m https github com evanli programming book raw master front end react pdf webgl front end webgl pdf download 81 26m https github com evanli programming book raw master front end webgl pdf web front end web pdf download 9 80m https github com evanli programming book raw master front end web pdf git github git github pdf download 20 31m https github com evanli programming book raw master git github pdf progit zh v2 1 16 git progit zh v2 1 16 pdf download 12 68m https github com evanli programming book raw master git progit zh v2 1 16 pdf | algorithm back-end database front-end git books | front_end |
HPCToolKit-GCP-CVS | hpctoolkit gcp cvs google cloud netapp volume allows organizations to harness the power of high performance scalable storage when combined with hpc toolkit this integration provides a robust infrastructure for running compute intensive and data intensive scientific and engineering applications | cloud |
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Machine_Learning_Journey | machine learning journey overview this is the curriculum for machine learning journey by siraj raval on youtube it starts with this https youtu be nmk94jlkrb4 video on youtube week 1 portfolio design creating a great resume https youtu be nmk94jlkrb4 social media for engineers https www youtube com watch v pulygf6trok lc ugwaemz65ziphvo5nv14aaabag how does github work https youtu be loav1kba640 live stream q a https www youtube com watch v zok0tpu0l4m week 2 mathematics backpropagation explained https www youtube com watch v fahhwdsiyqg loss functions explained https www youtube com watch v ivvvjbsk9n0 research paper to code https youtu be pqyzdwhbbqo 100 days of ml code challenge https www youtube com watch v cuqmbj1cwpo week 3 stock price prediction how to build a trading bot https www youtube com watch v f2f98pnj99k stock price prediction using reinforcement learning https www youtube com watch v 05nqkj0v7ee convolutional networks applied to time series data https www youtube com watch v 5uw1iswvhh8 your first machine learning api https www youtube com watch v yjyrbpz4com week 4 machine learning in practice aws explained https www youtube com watch v zkzed9hvmg0 feature youtu be completing a kaggle competition https www youtube com watch v surd3uzdbeo t 2245s google cloud explained https www youtube com watch v tdhvxkf wss azure explained https github com llsourcell azure machine learning week 5 machine learning languages best programming language for machine learning https www youtube com watch v cdxxrbkdho logistic regression in python https www youtube com watch v h6ii7nfddeg building an ml app with nodejs https www youtube com watch v cmank9ymttm school of ai introduction https www youtube com watch v 8yu8rtxthy8 week 6 modern day research neural arithmetic logic units https www youtube com watch v v9e7wg0dhiu openai five https www youtube com watch v dzzfsyzv1p0 alphago zero https www youtube com watch v uzyeqaj2ba8 t 204s pytorch live stream https www youtube com watch v tvwyv0viiqe week 7 studying practices how to study ml https www youtube com watch v waxhrc2m9k8 how to teach ml https www youtube com watch v tczjzolvjjm finding a local study group https www youtube com watch v 7tvma w8xw interview with ai researcher https youtu be rsopnfbufcy week 8 advanced topics quantum machine learning https www youtube com watch v dmzwsvb un4 low level optimization https youtu be gif8xoptmfg | ai |
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condenser | condenser condenser is the react js web interface to the world s first and best blockchain based social media platform steemit com it uses steem https github com steemit steem a blockchain powered by dpos governance and chainbase db to store json based content for a plethora of web applications why would i want to use condenser steemit com front end learning how to build blockchain based web applications using steem as a content storage mechanism in react js reviewing the inner workings of the steemit com social media platform assisting with software development for steemit com installation docker we highly recommend using docker to run condenser in production this is how we run the live steemit com site and it is the most supported and fastest method of both building and running condenser we will always have the latest version of condenser master branch available on docker hub configuration settings can be set using environment variables see configuration section below for more information if you need to install docker you can get it at https get docker com to bring up a running container it s as simple as this bash docker run it p 8080 8080 steemit condenser environment variables can be added like this bash docker run it p 8080 8080 steemit condenser if you would like to modify build and run condenser using docker it s as simple as pulling in the github repo and issuing one command to build it like this bash git clone https github com steemit condenser cd condenser docker build t myname condenser mybranch docker run it p 8080 8080 myname condenser mybranch building from source without docker the traditional way better if you re planning to do condenser development clone the repository and make a tmp folder bash git clone https github com steemit condenser cd condenser mkdir tmp install dependencies install at least node v8 7 if you don t already have it we recommend using nvm to do this as it s both the simplest way to install and manage installed version s of node if you need nvm you can get it at https github com creationix nvm https github com creationix nvm condenser is known to successfully build using node 8 7 npm 5 4 2 and yarn 1 3 2 using nvm you would install like this bash nvm install v8 7 we use the yarn package manager instead of the default npm there are multiple reasons for this one being that we have steem js built from source pulling the github repo as part of the build process and yarn supports this this way the library that handles keys can be loaded by commit hash instead of a version name and cryptographically verified to be exactly what we expect it to be yarn can be installed with npm but afterwards you will not need to use npm further bash npm install g yarn yarn global add babel cli yarn install frozen lockfile yarn run build to run condenser in production mode run bash yarn run production when launching condenser in production mode it will automatically use 1 process per available core you will be able to access the front end at http localhost 8080 by default to run condenser in development mode run bash yarn run start it will take quite a bit longer to start in this mode 60s as it needs to build and start the webpack dev server by default you will be connected to steemit com s public steem node at wss steemd steeemit com this is actually on the real blockchain and you would use your regular account name and credentials to login there is not an official separate testnet at this time if you intend to run a full fledged site relying on your own we recommend looking into running a copy of steemd locally instead https github com steemit steem https github com steemit steem debugging ssr code yarn debug will build a development version of the codebase and then start the local server with inspect brk so that you can connect a debugging client you can use chromium to connect by finding the remote client at chrome inspect devices configuration the intention is to configure condenser using environment variables you can see the names of all of the available configuration environment variables in config custom environment variables json default values are stored in config defaults json environment variables using an example like this bash export sdc client steemd url wss steemd steemit com export sdc server steemd url wss steemd steemit com keep in mind environment variables only exist in your active session so if you wish to save them for later use you can put them all in a file and source them in if you d like to statically configure condenser without variables you can edit the settings directly in config production json if you re running in development mode copy config production json to config dev json with cp config production json config dev json and adjust settings in dev json if you re intending to run condenser in a production environment one configuration option that you will definitely want to edit is server session secret which can be set by the environment variable sdc session secretkey to generate a new value for this setting you can do this bash node crypto randombytes 32 tostring base64 exit style guides for submitting pull requests file naming and location prefer camelcase js and jsx file names prefer lower case one word directory names keep stylesheet files close to components component s stylesheet file name should match component name js jsx we use prettier https github com prettier prettier to autofromat the code with this configuration prettierrc run yarn run fmt to format everything in src or yarn exec prettier config prettierrc write src whatever file js for a specific file css scss if a component requires a css rule please use its uppercase name for the class e g header class for the header s root div we adhere to bem methodology with exception for foundation classes here is an example for the header component html block ul class header element li class header menu item menu item 1 li element with modifier li class header menu item selected element with modifier li ul storybook yarn run storybook testing run test suite yarn test will run jest test endpoints offline if you want to test a server side rendered page without using the network do this yarn build offline ssr test true node env production node prof lib server index js this will read data from the blobs in api mockdata directory if you want to use another set of mock data create a similar directory to that one and add an argument offline ssr test data dir pointing to your new directory run blackbox tests using nightwatch to run a selenium test suite start the condenser docker image with a name condenser like docker run name condenser itp 8080 8080 steemit condenser latest and then run the blackboxtest image attached to the condneser image s network docker build t steemit condenser blackboxtest blackboxtest docker run network container condenser steemit condenser blackboxtest latest issues to report a non critical issue please file an issue on this github project if you find a security issue please report details to security steemit com we will evaluate the risk and make a patch available before filing the issue | steem-blockchain steemit react jsx social-network steem | blockchain |
choreo-examples | choreo examples this repository provides multiple examples for the choreo which is used for defining business processes these examples showcase the language s syntax and features and serve as a starting point for users to create their own choreo components | front_end |
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ember-mirage-quickstart | ember mirage quickstart this is work in progress the original readme provided with ember js is below my notes on setting up this app can be found in the file notes md notes md original ember js readme prerequisites you will need the following things properly installed on your computer git https git scm com node js https nodejs org with npm ember cli https cli emberjs com release google chrome https google com chrome installation git clone repository url this repository cd ember mirage quickstart npm install running development ember serve 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 npm run lint npm run lint fix building ember build development ember build environment production production deploying specify what it takes to deploy your app further reading useful links ember js https emberjs com ember cli https cli emberjs com release 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 | server |
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node-tutorial-for-frontend-devs | update this repo is no longer being maintained and i can t guarantee the code will continue to work although unless major changes happen to express it should the dead simple step by step guide for front end developers to getting up and running with node js express jade and mongodb a tutorial and complete sample project for front end developers showing how to get node express and jade up and running connected to mongodb and reading from writing to the database new updated for 2019 quickstart visit the tutorial online https closebrace com tutorials 2017 03 02 the dead simple step by step guide for front end developers to getting up and running with nodejs express and mongodb the rest of the project is provided just to show the functioning finished results the tutorial will show you how to build all of this stuff from downloading node all the way to the end if you want to run this example code you will need to do an npm install as the node modules directory has been removed from this repository you ll also need to set up a mongodb database i highly recommend just going through the tutorial author christopher buecheler is a web developer who runs closebrace https closebrace com a site that provides tutorials and training for full stack javascript developers previously he s worked for startups like gamespy okcupid crispy gamer goldenspear volt server tizra and datarista you can visit him at his website http cwbuecheler com contents public static directories suchs as images routes route files for tutorial project views views for tutorial project readme md this file app js central app file for tutorial project package json package info for tutorial project | front_end |
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aws-iot-examples | aws iot examples examples using aws iot internet of things this repository is now deprecated and will not receive further updates it was originally started in 2016 as a collection of samples for building with the brand new aws iot service most of the samples included have been made obsolete by more recent features or solutions sub bullets of the projects below link to better projects documentation or solutions which would likely better serve your interests mqttsample a reference implementation for connecting a web application to aws iot using mqtt over websockets the best practice for connecting to aws iot core in a browser application is to use aws amplify https aws amazon com amplify alternatively check out the aws iot device sdk for javascript which includes some browser examples https github com aws aws iot device sdk js tree master examples browser trucksimulator sample code for simulating an internet connected truck sending location and performance metrics to aws iot or an aws iot device shadow for standing up device simulators see the iot device simulator https aws amazon com solutions iot device simulator solution predictiondatasimulator python script which simulates publishing prediction data for a sample integration between aws iot and amazon machine learning this sample predates the launch of amazon sagemaker check out this sample project https github com aws samples amazon sagemaker aws greengrass custom timeseries forecasting for getting started with predictive maintenance using aws iot and amazon sagemaker features devicesimulator cloudformation template and lambda function for publishing device data as a simulator to aws iot for standing up device simulators see the iot device simulator https aws amazon com solutions iot device simulator solution justintimeregistration sample lambda function code that creates and attaches an iot policy to the just in time registered certificate it also activates the certificate the lambda function is attached as a rule engine action to the registration topic aws events certificates registered lt cacertificateid gt this sample is still suitable for just in time registration but you may be interested in some additional device provisioning features https docs aws amazon com iot latest developerguide iot provision html that have launched since this sample was created such as just in time provisioning bulk provisioning and fleet provisioning heregeofencingrule sample lambda function code that utilizes here geofencing capabilities add this as an in line function call in your aws iot topic rule to build geofencing evaluation into your rule at run time the pattern expressed in this example is still sound for demonstrating how an iot core rule can integrate with a third party api using an aws lambda function the pdf documentation includes outdated screenshots of the aws management console experience at least one major version of the here api has been released since this sample was created you may wish to review the latest developer documentation https developer here com documentation first | server |
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simplecv-demo | simplecv demos code to accompany a talk to the foundations of computing class at the university of melbourne requirements you should install simplecv requires opencv numpy ipython notebook running the examples the examples are numbered so that you can build from simple cases to more advanced ones for ipynb files open them in the ipython notebook run ipython notebook in the same folder if you don t have ipython installed you can read them online at 00 image basics http nbviewer ipython org github larsyencken simplecv demo blob master 00 image basics ipynb 03 image operations http nbviewer ipython org github larsyencken simplecv demo blob master 03 image operations ipynb for py files just run them directly in shell python myscript py useful references simplecv http www simplecv org simplecv help forum http help simplecv org questions simplecv pycon 2013 talk http simplecv org news 2013 03 simplecv talk pycon video 26 mins simplecv pycon 2013 tutorial http www simplecv org news 2013 03 simplecv tutorial pycon 0 video 3 hours example image sources msdn color http msdn microsoft com en us library windows desktop aa511283 aspx source of rgb cube jpg and hsv cone jpg pinterest pin rainbow cake http pitereset pin blogspot com 2013 01 rainbow cake html source of rainbow cake jpg prison cat found with cellphone small saws in brazil http www heavy com news 2013 01 prison cat cellphone saws source of prizon cat jpg wikimedia commons http commons wikimedia org wiki file all gizah pyramids jpg source of gizah jpg bitdeli badge https d2weczhvl823v0 cloudfront net larsyencken simplecv demo trend png https bitdeli com free bitdeli badge | ai |
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it-pat-2023-complete | it pat 2023 my matric information technology practical | server |
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Hands-on-Engineering-Data-Mesh-in-Azure-Cloud | hands on engineering data mesh in azure cloud hands on engineering data mesh in azure cloud | cloud |
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employee-manager-backend | employee manager application app to manage employees using crud create read update and delete operations a spring boot web application for managing employee information this application covers spring boot and mysql using spring data jpa and also dives into defining and creating a spring boot api exposing api endpoints over http and handling http requests through api endpoints features view and edit employee information add and delete employees search for employees by name or department getting started 1 clone the repository git clone https github com ramkishore417 employeemanager git 2 build the project mvn clean install 3 run the application mvn spring boot run 4 access the application at http localhost 8080 prerequisites java 8 or later maven mysql configuration the application uses mysql as the database you will need to configure the database connection in the application properties file located in src main resources built with java spring boot spring rest spring data jpa mysql authors ramkishore https github com ramkishore417 ramkishore | java spring-boot spring-mvc | server |
Hospital-Management-System | hospital management system this is the laboratory mini project of the database management system laboratory course of department of computer science and engineering iit kharagpur for the spring semester 2022 23 backend the backend is written in python using the flask framework the database used is postgresql generate the requirements txt file using the following command pip install pipreqs pipreqs force install the requirements using the following command pip install r requirements txt install postgresql | server |
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cssmastery | cssmastery 1 intro intro 1 selectors selectors 1 overview 1 specificity intro 1 relational selectors combinators 1 selectors api 1 attribute selectors 1 ui pseudo class selectors 1 structural selectors 1 other logical combinations negation matching and parent 1 language based selectors 1 link location user action pseudo classes 1 additional pseudo classes 1 specificity revisited 1 pseudo elements selectors index html slide79 1 first letter 1 first line 1 selection 1 before after and generated content 1 selection 1 additional pseudo elements 1 browser specific pseudo elements 1 generated content generated 1 how before and after work 1 how generated content works 1 generated content quotes 1 generated content attribute values 1 generated content counters 1 generated content images 1 generated content strings 1 special characters 1 accessibility 1 design elements 1 media queries media 1 media type screen size resolution 1 browser capability supports 1 viewport 1 use cases hyphenations columns svg 1 colors appearance colors 1 colors 1 opacity v alphatransparency 1 appearance 1 additional pseudo elements 1 flexbox flexbox 1 purpose and goal of flexbox 1 browser support and specification 1 overview 1 the basics 1 flex container properties 1 flex item properties 1 flexibility 1 tables tables 1 when to use 1 semantics 1 caption 1 border padding spacing 1 other table properties 1 styling columns 1 good ui 1 grid grid 1 overview flex v grid 1 basic grid 1 display property 1 defining columns and rows 1 fr unit and repeat notation 1 adding gutters 1 try it out 1 positioning grid items 1 container properities 1 align and justify items 1 align and justify content 1 backgrounds and borders borders 1 overview 1 background properties 1 background color 1 old background shorthand for single image 1 overview of added properties 1 background image 1 background repeat 1 background attachment 1 background position 1 background clip 1 background origin 1 background size 1 background shorthand 1 gradients gradients 1 overview 1 syntax 1 color stops 1 color hints 1 directions 1 keyterms 1 angles 1 examples exercise 1 repeating linear gradients 1 radial gradients 1 position 1 size shape 1 radial gradients color stops color hints 1 repeating radial gradient 1 transforms transforms 1 overview 1 2d transform functions 1 order of functions 1 transform origin 1 3d transform funtions 1 3d transform related properties 1 perspective 1 perspective origin 1 transform origin 1 transform style 1 transform box 1 transitions animations 1 overview 1 transition properties 1 properties that can be animated 1 need to knows 1 events 1 animations animations 1 overview 2 keyframes 3 animation properties 2 specificity 1 timing functions 1 steps 1 iteration count 1 delays 1 direction 1 shorthand 1 animation fill mode 1 stopping animations 1 events | front_end |
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condenser | condenser condenser is the react js web interface to the world s first and best blockchain based social media platform steemit com it uses steem https github com steemit steem a blockchain powered by dpos governance and chainbase db to store json based content for a plethora of web applications why would i want to use condenser steemit com front end learning how to build blockchain based web applications using steem as a content storage mechanism in react js reviewing the inner workings of the steemit com social media platform assisting with software development for steemit com installation docker we highly recommend using docker to run condenser in production this is how we run the live steemit com site and it is the most supported and fastest method of both building and running condenser we will always have the latest version of condenser master branch available on docker hub configuration settings can be set using environment variables see configuration section below for more information if you need to install docker you can get it at https get docker com to bring up a running container it s as simple as this bash docker run it p 8080 8080 steemit condenser environment variables can be added like this bash docker run it p 8080 8080 steemit condenser if you would like to modify build and run condenser using docker it s as simple as pulling in the github repo and issuing one command to build it like this bash git clone https github com steemit condenser cd condenser docker build t myname condenser mybranch docker run it p 8080 8080 myname condenser mybranch building from source without docker the traditional way better if you re planning to do condenser development clone the repository and make a tmp folder bash git clone https github com steemit condenser cd condenser mkdir tmp install dependencies install at least node v8 7 if you don t already have it we recommend using nvm to do this as it s both the simplest way to install and manage installed version s of node if you need nvm you can get it at https github com creationix nvm https github com creationix nvm condenser is known to successfully build using node 8 7 npm 5 4 2 and yarn 1 3 2 using nvm you would install like this bash nvm install v8 7 we use the yarn package manager instead of the default npm there are multiple reasons for this one being that we have steem js built from source pulling the github repo as part of the build process and yarn supports this this way the library that handles keys can be loaded by commit hash instead of a version name and cryptographically verified to be exactly what we expect it to be yarn can be installed with npm but afterwards you will not need to use npm further bash npm install g yarn yarn global add babel cli yarn install frozen lockfile yarn run build to run condenser in production mode run bash yarn run production when launching condenser in production mode it will automatically use 1 process per available core you will be able to access the front end at http localhost 8080 by default to run condenser in development mode run bash yarn run start it will take quite a bit longer to start in this mode 60s as it needs to build and start the webpack dev server by default you will be connected to steemit com s public steem node at wss steemd steeemit com this is actually on the real blockchain and you would use your regular account name and credentials to login there is not an official separate testnet at this time if you intend to run a full fledged site relying on your own we recommend looking into running a copy of steemd locally instead https github com steemit steem https github com steemit steem debugging ssr code yarn debug will build a development version of the codebase and then start the local server with inspect brk so that you can connect a debugging client you can use chromium to connect by finding the remote client at chrome inspect devices configuration the intention is to configure condenser using environment variables you can see the names of all of the available configuration environment variables in config custom environment variables json default values are stored in config defaults json environment variables using an example like this bash export sdc client steemd url wss steemd steemit com export sdc server steemd url wss steemd steemit com keep in mind environment variables only exist in your active session so if you wish to save them for later use you can put them all in a file and source them in if you d like to statically configure condenser without variables you can edit the settings directly in config production json if you re running in development mode copy config production json to config dev json with cp config production json config dev json and adjust settings in dev json if you re intending to run condenser in a production environment one configuration option that you will definitely want to edit is server session secret which can be set by the environment variable sdc session secretkey to generate a new value for this setting you can do this bash node crypto randombytes 32 tostring base64 exit style guides for submitting pull requests file naming and location prefer camelcase js and jsx file names prefer lower case one word directory names keep stylesheet files close to components component s stylesheet file name should match component name js jsx we use prettier https github com prettier prettier to autofromat the code with this configuration prettierrc run yarn run fmt to format everything in src or yarn exec prettier config prettierrc write src whatever file js for a specific file css scss if a component requires a css rule please use its uppercase name for the class e g header class for the header s root div we adhere to bem methodology with exception for foundation classes here is an example for the header component html block ul class header element li class header menu item menu item 1 li element with modifier li class header menu item selected element with modifier li ul storybook yarn run storybook testing run test suite yarn test will run jest test endpoints offline if you want to test a server side rendered page without using the network do this yarn build offline ssr test true node env production node prof lib server index js this will read data from the blobs in api mockdata directory if you want to use another set of mock data create a similar directory to that one and add an argument offline ssr test data dir pointing to your new directory run blackbox tests using nightwatch to run a selenium test suite start the condenser docker image with a name condenser like docker run name condenser itp 8080 8080 steemit condenser latest and then run the blackboxtest image attached to the condneser image s network docker build t steemit condenser blackboxtest blackboxtest docker run network container condenser steemit condenser blackboxtest latest issues to report a non critical issue please file an issue on this github project if you find a security issue please report details to security steemit com we will evaluate the risk and make a patch available before filing the issue | steem-blockchain steemit react jsx social-network steem | front_end |
PeakPerformanceAthletics | installing dependencies in order to run this flask app activate the virtual environment of your choice then run pip install r requirements txt this will install all the requirements needed to run the flask app in order to actually run the app navigate to the base repository directory your current directory should contain main py run the following flask app main run the command line will output the port on which the website is running uploading files csv files can be uploaded from the path upload an uploaded file will be automatically parsed and ingested into the database in order for the file to be properly parsed and inserted the following conventions must be followed the filename must be in user csv nutrition csv or of the form recovery name csv sleep name csv hawkins name csv uploaded files currently overwrite the previous csv of the same name this should be changed in a later version the csv file must contain the correct column labels cs321 milestone5 h2 deployment to cloud h2 abstract this milestone involved developing a dynamic version of our athletic management system to the cloud we relied on our work from milestone 4 flask website as a base for adding new functional features from our backlog this included using biometric data and updating our graphs and tables to reflect this and deploying our app to the cloud our plan was in the form of issues as follows host the app on the cloud use real data in the data base refactor the format of our html files add fields to database objects aggregate our data use real data in our graphs and tables revamp our sign up functionality sprint backlog user stories general p update this once milestone is completed p p as a user i can create a new account using an email and password completed br as a user of the website i can log in to the website with a username and password completed br as a user of the website i can login to my assigned role completed br as a user of the website i can navigate back to my dashboard by clicking on the mule icon partially completed works for moving between athlete detail pages and dashboard p admin peak p as an admin i can log in with user name and password completed br as an admin after logging in i can navigate to my dashbord completed br as an admin i can view my dashbord on the website completed br as an admin i can view all of the sports teams in the teams table completed br as an admin i can edit one file teamnames csv to change what teams appear on my dashboard completed br as an admin when i click on a team name i will be redirected to the associated team view page completed br as an admin on my team view pages i can see team name team data and a list athletes of that team completed br as an admin when on team view i can click on an athlete s name and be redirected to the corresponding athlete view page complete br as an admin on my view of athletes i can see their name their sports science data and important notes about the athlete complete at a basic stage all athletes have same data br p athlete coach results img width 1000 alt screen shot 2022 11 09 at 10 13 35 pm src https user images githubusercontent com 30237570 200992076 42d2d240 6ee6 4633 823a 02f36a289872 png updated graphs as shown in athlete dashboard illustrating real data from our database admin views in order dashboard team view athlete view img width 1000 src https user images githubusercontent com 113453620 201239056 b402fd8e fefc 4203 9212 148b793bf394 png img width 1000 src https user images githubusercontent com 113453620 201239357 e14a083f ec3f 4188 817e 7734b138731e png img width 1000 src https user images githubusercontent com 113453620 201239424 175d86d6 3c6c 49db b15c f678593031fa png burn down chart image https user images githubusercontent com 70499767 201227693 4671b947 abd1 4442 88c2 5338610a85f5 png team reflection contribution list calvin reformatted the data classes in models py and reviewed pull requests to resolve conflicts in merging created the burndown chart for this milestone matt worked on parsing csv files into objects in our database with parameters for each of the columns ben worked on setting up flask security and email confirmation password reset hannah worked on fixing bugs in permissions milo added a config file and a secret key to the repo to enable cloud deployment configured a free account and webapp service on microsoft azure to enable cloud hosting of our application helped troubleshoot with other developers and took the lead on reviewing pull requests tamsin connected database to plotly graphs reconstructed subplots to individual graphs made appropriate edits in html dashboard files nicole extensions we added a functional readme file to our repository detailing the website references naser al madi cs321 milestone6 h2 ci cd testing h2 abstract this milestone involved developing a ci cd pipeline to lint test and deploy a dynamic version of our athletic management system to the cloud the updates made to our flask website in this milestone build on top of the previous milestone milestone 5 and add tests along with new functional features from our backlog burn down chart image https user images githubusercontent com 70499767 203463894 b320b703 75f4 4ac1 8064 d4b713cb1b0e png team reflection p this week we worked on our communication and by the latter half of the milestone we made some good progress our issues we made sure to be smaller so that each team member was able to make progress on a number of individual issues our meeting to get our develop branch working took longer than it should have because we didn t fully respect every team member s ideas we also had two team members leave our group without making clear that they had which made finishing the issues they were assigned much more difficult p sprint backlog user stories general p as a user i can login with my email and password completed p admin peak p as an admin i can view the averages of all of the athletes data completed br as an admin i can see a breakdown of all of the teams average data completed br as an admin i can add new users partially complteded anyone can do this through the upload file but adding a user in the permissions page does not fully work br p athlete p as an athlete i can view my recent data completed br as an athlete i can view a history of my data partially completed only readiness is shown br p coach p as a coach i can view data on my team as a whole completed br as a coach i can see my athlete s breakdowns for my team completed br as a coach i can click on an athlete and see their specific data completed br p results contribution list calvin reviewed and resolved pull requests wrote but not finished at time of sprint end functional tests for athlete data views on nutrition readiness and sleep quality created the burndown chart matt added continuous integration made permissions page more accurate made admins be able to view all of the teams and their data averages added functinality to coach s view to see athletes of their team and the athletes data worked on setting up a functional database added function to populate empty database was scrum master for this milestone ben milo wrote several functional unit tests deployed the website to the web publicly and created another develop deployment slot for testing tamsin wrote code to pull database data into views py for use in adminview teamview and athleteview graphs fixed general css layout bugs throughout the website edited html redirects to appropriate data view pages extensions we added a functional readme file to our repository detailing the website references naser al madi cs321 milestone7 h2 api integration h2 abstract this milestone involved researching apis to pull data from wearable devices into our app an api is a set of functions and procedures allowing the creation of applications that access the features or data of an operating system application or other service we focused on the google drive api and learned a lot from the example we went over in class last week burn down chart image https user images githubusercontent com 70499767 206769461 efc745ac e992 4b4b 9a0f e4c8c4d6f304 png team reflection p we continued implementing our goals in the form of smaller issues and assigned these issues early on so that it was clear what was expected of each team member during the milestone our testing practices also improved during this milestone and our communication via pull requests and git comments was good this week we split assignments and time between working on integrating the apis developing new features and fixing bugs from previous milestones we hope to improve our work and add even more functional features for the version submission of our system we also experienced some difficulty this week due to our azure subscription being discontinued we had to rush to start moving things over to heroku at the last minute so this project is still a work in progress p sprint backlog user stories general p as a user i can login with my email and password completed p admin peak p as an admin i can view the averages of all of the athletes data completed br as an admin i can see a breakdown of all of the teams average data completed br as an admin i can add new users completed br as an admin i can remove users completed br p athlete p as an athlete i can view my recent data completed br as an athlete i can view a history of my readiness data completed br p coach p as a coach i can view the averages of all of my team s data completed br as a coach i can see a breakdown for each individual athlete on my team completed br as a coach i can view a history of my team s readiness data data completed br p results p login screen p p img width 1438 alt screen shot 2022 12 09 at 10 06 11 am src https user images githubusercontent com 30237570 206731905 6c55a0bd 0154 42ac 8b12 4b87a5773b0b png p p admin dashboard p p img width 1429 alt screen shot 2022 12 09 at 10 07 03 am src https user images githubusercontent com 30237570 206732105 4e5b46b4 7506 488c 8a6b 933492e872e8 png p p permissions dashboard p p img width 1423 alt screen shot 2022 12 09 at 10 10 43 am src https user images githubusercontent com 30237570 206732809 6f91b55d 861f 4f27 b428 05f8d02fdb8e png p p add users p p img width 1429 alt screen shot 2022 12 09 at 10 11 15 am src https user images githubusercontent com 30237570 206732941 344c5ca3 afc2 42b1 a4b8 41d1b2ed6e32 png p p remove users p p img width 1433 alt screen shot 2022 12 09 at 10 11 52 am src https user images githubusercontent com 30237570 206733056 38b57ce5 6c63 4b49 b550 fc1493513f32 png p p upload data admin only p p img width 1424 alt screen shot 2022 12 09 at 10 12 17 am src https user images githubusercontent com 30237570 206733137 659cfe05 a788 4e5a a7b0 6926c6453a96 png p p improved methods of switching between teams search bar and dropdown menu p p img width 772 alt screen shot 2022 12 12 at 6 18 56 pm src https user images githubusercontent com 30237570 207180560 5b83f695 975c 4ebc 99c9 0fc58e3c4192 png p p img width 339 alt screen shot 2022 12 12 at 6 19 02 pm src https user images githubusercontent com 30237570 207180571 9b7ecf55 5d0f 4f8c 94f3 f72d4bd281f3 png p p coach dashboard p p img width 1428 alt screen shot 2022 12 12 at 6 18 32 pm src https user images githubusercontent com 30237570 207180514 0c32ee17 531e 452e a761 7840ce5e7da6 png p p athlete dashboard p p img width 1430 alt screen shot 2022 12 12 at 6 18 45 pm src https user images githubusercontent com 30237570 207180502 eb38d2a0 dc5d 43fa b6fe c22c403f8bf8 png p contribution list calvin implemented more tests to increase test coverage and ensure quality code created both funtional and unit tests and added the burndown chart matt ben milo implemented google drive api capabilities tamsin scrum master wrote and assigned new issues researched google drive myfitnesspal oura ring hawkins and fitbits apis improved documentation implemented a dropdown menu in the dashboard header to allow users with multiple teams to switch between their teams made slides to introduce project presentation anton extensions functional readme file to our repository detailing the website extensive documentation in all files to improve coherence implemented functionality to remove users implemented functionality to send login recovery emails for improved security added more ui features for increased accessibility search bar dropdown menu to switch between teams references naser al madi cs321 milestone8 h2 refactoring better design h2 abstract this milestone involved refactoring and enhancing the quality of our software by focussing on design patterns and anti patterns we implemented remaining items in our product backlog and refactored our code to enhance readability and maintainability we strove to implement multiple apis maintain a test coverage above 90 and reduce the complexity of our code by refactoring it as measured by code metrics this milestone also involved the use of radon a python tool for calculating code metrics to calculate cyclomatic complexity and maintainability index for our code before and after refactoring with the before calculations being from the repository submitted for milestone 7 burn down chart p p img width 1000 alt burndown chart 8 src https user images githubusercontent com 70499767 208593734 867662c6 9322 4288 be2d f35a992dab5e png p p team reflection p p sprint backlog user stories general p as a user i can login with my email and password completed p p as a user i can use my email for account recovery completed p admin peak p as an admin i can view the averages of all of the athletes data completed br as an admin i can see a breakdown of all of the teams average data completed br as an admin i can add new users completed br as an admin i can remove users completed br p athlete p as an athlete i can view my recent data completed br as an athlete i can view a history of my readiness data completed br p coach p as a coach i can view the averages of all of my team s data completed br as a coach i can see a breakdown for each individual athlete on my team completed br as a coach i can view a history of my team s readiness data data completed br p results p radon results before refactoring p p img width 1125 alt screen shot 2022 12 18 at 9 39 40 pm src https user images githubusercontent com 30237570 208337158 86cf07da aa60 4383 b2e7 17742b85983e png p p radon results after refactoring p p latest commit number 214cb3a1695f3d94b0335d2f5fe1ab498451ddd9 p p cyclomatic complexity p p img width 650 alt screen shot of radon src https user images githubusercontent com 70499767 208593342 48856997 bef5 4408 b8f4 5b9bd4371825 png p p img width 650 alt screenshot of radon two src https user images githubusercontent com 70499767 208593496 03935346 9f8b 4dc1 b7cf 15a66467c40c png p p p p maintainability index p p img width 650 alt screenshot of radon three src https user images githubusercontent com 70499767 208593582 13dfae9b ed6a 48e3 ba84 5ac37f81fa27 png p contribution list calvin created burndown chart reviewed pull requests added more testing and added post refactor radon output matt ben refactored graph code to reduce length of views py set up heroku deployment here https colby athlete managment system herokuapp com created oauth py to handle oauth2 flow milo increased test coverage by 11 configured pytest and radon with custom repository commands collected code complexity metrics and refactored views and auth tamsin scrum master wrote and posted issues for new milestone fixed team breakdown table to reflect real data improved formatting in athlete breakdown table fixed bug where roles were not being assigned user table was not being created cleaned up name variables to standardize capitalization and spacing cleaned up and linted code connected dashboard stats table to database so it reflects real changes in data over time connected coach schedule to google calendar anton new feature summary functional heroku deployment img width 1411 alt screen shot 2022 12 19 at 5 40 27 pm src https user images githubusercontent com 30237570 208540616 9bc46432 e131 4bbe bc04 d09092755f1c png dashboard stats table now reflects real database data img width 1299 alt screen shot 2022 12 19 at 5 41 57 pm src https user images githubusercontent com 30237570 208540837 d5d8b2e5 836c 4ce9 b1ad cc7da02e0835 png functional unit tests for new features connected google drive api to database extensions functional readme file to our repository detailing the website references naser al madi | server |
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eeplat | eeplat paas eeplat eeplat eeplat eeplat | front_end |
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python-toolz | python toolz v0 1 9 zguillez https zguillez io guillermo de la iglesia python helpers getting started install pip install upgrade python toolz usage from python toolz import helper as ztools ztools log test db ztools database conn os environ db host database os environ db name user os environ db user password os environ db pass data db sql select id name from template order by id asc limit 0 5 db close print data 0 data db dict select id name from template order by id asc limit 0 5 id name db close print data 0 name contributing and issues contributors are welcome please fork and send pull requests if you have any ideas on how to make this project better then please submit an issue or email mailto guillermo delaiglesia email me license 2023 zguillez io original code licensed under mit https en wikipedia org wiki mit license open source projects used within this project retain their original licenses changelog v0 1 0 february 11 2023 initial commit | developer-tools helper python | server |
rt-thread | p align center img src documentation figures logo png width 60 p english readme zh md espa ol readme es md deutsch readme de md githubstars https img shields io github stars rt thread rt thread style flat square logo github https github com rt thread rt thread stargazers giteestars https gitee com rtthread rt thread badge star svg theme gvp https gitee com rtthread rt thread stargazers github https img shields io github license rt thread rt thread svg https github com rt thread rt thread blob master license github release https img shields io github release rt thread rt thread svg https github com rt thread rt thread releases gitter https badges gitter im join 20chat svg https gitter im rt thread rt thread utm source badge utm medium badge utm campaign pr badge utm content badge github pull requests https img shields io github issues pr rt thread rt thread svg https github com rt thread rt thread pulls prs welcome https img shields io badge prs welcome brightgreen svg style flat https github com rt thread rt thread pulls rt thread rt thread was born in 2006 it is an open source neutral and community based real time operating system rtos rt thread is mainly written in c language easy to understand and easy to port can be quickly port to a wide range of mainstream mcus and module chips it applies object oriented programming methods to real time system design making the code elegant structured modular and very tailorable rt thread has standard version and nano version for resource constrained microcontroller mcu systems the nano version that requires only 3kb flash and 1 2kb ram memory resources can be tailored with easy to use tools for resource rich iot devices rt thread can use the on line software package management tool together with system configuration tools to achieve intuitive and rapid modular cutting seamlessly import rich software packages thus achieving complex functions like android s graphical interface and touch sliding effects smart voice interaction effects and so on rt thread architecture rt thread has not only a real time kernel but also rich components its architecture is as follows architecture documentation figures architecture png it includes kernel layer rt thread kernel the core part of rt thread includes the implementation of objects in the kernel system such as multi threading and its scheduling semaphore mailbox message queue memory management timer etc libcpu bsp chip migration related files board support package is closely related to hardware and consists of peripheral drivers and cpu porting components and service layer components are based on upper level software on top of the rt thread kernel such as virtual file systems finsh command line interfaces network frameworks device frameworks and more its modular design allows for high internal cohesion inside the components and low coupling between components rt thread software package https packages rt thread org en index html a general purpose software component running on the rt thread iot operating system platform for different application areas consisting of description information source code or library files rt thread provides an open package platform with officially available or developer supplied packages that provide developers with a choice of reusable packages that are an important part of the rt thread ecosystem the package ecosystem is critical to the choice of an operating system because these packages are highly reusable and modular making it easy for application developers to build the system they want in the shortest amount of time rt thread supports 450 software packages rt thread features designed for resource constrained devices the minimum kernel requires only 1 2kb of ram and 3 kb of flash a variety of standard interfaces such as posix cmsis c application environment has rich components and a prosperous and fast growing package ecosystem elegant code style easy to use read and master high scalability rt thread has high quality scalable software architecture loose coupling modularity is easy to tailor and expand supports high performance applications supports all mainstream compiling tools such as gcc keil and iar supports a wide range of a href https www rt thread io board html architectures and chips a code catalogue rt thread source code catalog is shown as follow name description bsp board support package based on the porting of various development boards components components such as finsh shell file system protocol stack etc documentation related documents like coding style doxygen etc examples related sample code include head files of rt thread kernel libcpu cpu porting code such as arm mips risc v etc src the source files for the rt thread kernel tools the script files for the rt thread command build tool rt thread has now been ported for nearly 200 development boards most bsps support mdk iar development environment and gcc compiler and have provided default mdk and iar project which allows users to add their own application code directly based on the project each bsp has a similar directory structure and most bsps provide a readme md file which is a markdown format file that contains the basic introduction of bsp and introduces how to simply start using bsp resources supported architectures rt thread supports many architectures and has covered the major architectures in current applications architecture and chip manufacturer involved arm cortex m0 m0 manufacturers like st arm cortex m3 manufacturers like st winner micro mindmotion ect arm cortex m4 manufacturers like st infineon nuvoton nxp nordic https github com rt thread rt thread tree master bsp nrf5x gigadevice realtek ambiq micro ect arm cortex m7 manufacturers like st nxp arm cortex m23 manufacturers like gigadevice arm cortex m33 manufacturers like st arm cortex r4 arm cortex a8 a9 manufacturers like nxp arm7 manufacturers like samsung arm9 manufacturers like allwinner xilinx goke arm11 manufacturers like fullhan mips32 manufacturers like loongson ingenic risc v rv32e rv32i f rv64 d manufacturers like sifive canaan kendryte https github com rt thread rt thread tree master bsp k210 bouffalo lab https github com rt thread rt thread tree master bsp bouffalo lab nuclei https nucleisys com t head https www t head cn hpmicro https github com rt thread rt thread tree master bsp hpmicro arc manufacturers like synopsys dsp manufacturers like ti c sky x86 supported ide and compiler the main ide compilers supported by rt thread are rt thread studio ide mdk keil iar gcc rt thread studio ide user manual https www rt thread io document site rtthread studio um studio user manual tutorial videos https youtu be ucq5ejgziqg rt thread studio ide a k a rt studio is a one stop intergrated development environment built by rt thread team it has a easy to use graphical configuration system and a wealth of software packages and components resources rt studio has the features of project creation configuration and management as well as code editing sdk management build configuration debugging configuration program download and debug we re looking to make the use of rt studio as intuitive as possible reducing the duplication of work and improving the development efficiency studio documentation figures studio gif env tool user manual documentation env env md tutorial videos https www youtube com watch v dek94o yoso in the early stage rt thread team also created an auxiliary tool called env it is an auxiliary tool with a tui text based user interface developers can use env tool to configure and generate the gcc keil mdk and iar projects env documentation figures env png getting started rt thread programming guide https www rt thread io document site tutorial quick start introduction introduction rt thread studio ide https www rt thread io studio html kernel sample https github com rt thread packages kernel sample rt thread beginners guide https www youtube com watch v zmi1o rr7yc list plxuv89c m3g5kvw2ieri pqapdsm iazo based on stm32f103 bluepill https github com rt thread rt thread tree master bsp stm32 stm32f103 blue pill raspberry pi pico https github com rt thread rt thread tree master bsp raspberry pico simulator rt thread bsp can be compiled directly and downloaded to the corresponding development board for use in addition rt thread also provides qemu vexpress a9 bsp which can be used without hardware platform see the getting started guide below for details getting started of qemu with env windows documentation quick start quick start qemu quick start qemu md linux ubuntu documentation quick start quick start qemu quick start qemu linux md mac os documentation quick start quick start qemu quick start qemu macos md license rt thread follows the apache license 2 0 free software license it s completely open source can be used in commercial applications for free does not require the disclosure of code and has no potential commercial risk license information and copyright information can generally be seen at the beginning of the code c copyright c 2006 2018 rt thread development team spdx license identifier apache 2 0 community rt thread is very grateful for the support from all community developers and if you have any ideas suggestions or questions in the process of using rt thread rt thread can be reached by the following means and we are also updating rt thread in real time on these channels at the same time any questions can be asked in the issue section of rt thread repository https github com rt thread rt thread issues or rt thread forum https club rt thread io and community members will answer them website https www rt thread io github https github com rt thread rt thread twitter https twitter com rt thread linkedin https www linkedin com company rt thread iot os posts feedview all youtube https www youtube com channel ucddhtifsypq4002r27ffqpw facebook https www facebook com rt thread iot os 110395723808463 modal admin todo tour medium https rt thread medium com contribution if you are interested in rt thread and want to join in the development of rt thread and become a code contributor please refer to the code contribution guide documentation contribution guide contribution guide md thanks for the following contributors a href https github com rt thread rt thread graphs contributors img src https contrib rocks image repo rt thread rt thread a | china embedded-systems kernel iot rtos arm cortex-m cortex-a risc-v mips microcontroller microkernel real-time aiot | server |
ECE_387_Midterm_IB | ece 387 midterm ib embedded systems design midterm project | os |
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SED-Web-Application | sed web registration application development this program is in development and is to be used for the mitre scout engineering day as a registration web service the front end of the registration service and is written in html javascript python and css with the database using mysql anyone who would like to help with development please contact ryan dufrene at rdufrene mitre org or walter hiranpat at whiranpat mitre org please review the license code of conduct and contributing documentation installation the installation of this web application is done using the scoutengineeringday sed deployments https github com scoutengineeringday sed deployments repository please review the instillation instructions found there recompiling website code after making changes to the code located in your location choice sed deployments content sed web application you will notice that the website will not automatically update the following steps will update the local delpyment of the website 1 open command line of your choosing 2 enter the folder that holds the repository cd your location choice sed deployments 3 ssh into the vagrant mechine vagrant ssh 4 enter the code source ansible 5 run the update script sed web update sh wait for the site to recompile and then refresh http localhost 8080 http localhost 8000 urls local host urls http localhost 8080 http localhost 8000 local website home page http localhost 8080 admin http localhost 8000 admin local admin page main test website url http www sedteam com http www sedteam com website home page http www sedteam com admin http www sedteam com admin website admin page contributing before contributing please make sure you meet the requirements stated in the contributing md file process to contribute as non member of the team 1 fork the project 2 create your feature branch git checkout b my new feature 3 commit your changes git commit am add some feature 4 push to the branch git push origin my new feature 5 submit a pull request design sed software png sed software png raw true scout engineering day web design database design schema sed database jpg sed database jpg raw true scout engineering day database credits developer team 2016 sue kim manager initial work ryan dufrene front end developer initial work walter hiranpat aws django back end developer database developer initial work edward gedeon front end developer initial work developer team 2017 sue kim ryan dufrene walter hiranpat phillip marlow kaylee white joseph mahakian joel stien developer team 2018 sue kim managment ryan dufrene front end walter hiranpat back end phillip marlow deployment kaylee white design kevin codera test | server |
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biomutant-speedrun-reverse-engineering | biomutant speedrun reverse engineering db database to keep track of reversed stuff from time to time this will be filled with content if you want commit content tell me on discord xnyu 6036 and i will grant you access to this repo | server |
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Breakout-RC-car | breakout rc car final project for embedded system design coded by chunguang eric xie and shangrong li this the final project for embedded system design using tiva tm4c123 micro controller with two motor drivers four motors bluetooth lcd touchable screen and external charger as power supply the system is coded fully in rtos the player would not be able to control the rc car until they finish a breakout game the game has a random trophy if the player got the trophy he she could touch the screen to choose between car operating or continue game if car operating is chosen the player could use his her smart phone to control the rc car using bluetooth if continue game is chosen the player could continue to play the breakout game demo video available here https drive google com drive folders 10ofchmsspa3ozakmuzwbmh6ov239uilf usp sharing have fun | os |
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carpc | carpc an in dash interface designed to run on embedded linux systems | os |
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3dcv-students | exercises for 3d computer vision requirements python 3 installation unix for the installation i recommend a python venv sh git clone git github com vislearn 3dcv students git cd 3dcv python3 m venv source bin activate pip install r requirements txt windows download python here https www python org downloads windows make sure that the installer adds python to your path in powershell run bat git clone git github com vislearn 3dcv students git if you don t use git just download and extract the zip file bat cd 3dcv pip install torch torchvision f https download pytorch org whl torch stable html pip install r requirements txt usage in order to edit the notebooks run sh jupyter lab to start the local webserver if the notebook home page does not show up immediately open http localhost 8888 in your browser now just open one of the task notebooks and start editing project organization 1 0 tl scientific python ipynb the notebooks containing your tasks license the license readme md the top level readme with installation instructions data the necessary data files e g datasets models trained and serialized models model predictions or model summaries requirements txt the requirements file to setup the environment task pdf detailed information about your tasks vll boilerplate source code provided by us data scripts to download or generate data model scripts defining the neural network models utils scripts utilities used during data generation or training validate scripts to validate models visualize scripts to create exploratory and results oriented visualizations | ai |
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next-express-boilerplate | next react boilerplate nextjs express boilerplate with mvc architecture | server |
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TTK4155 | ttk4155 embedded and industrial computer systems design fall 18 k olsen kimisak https github com kimisak s olsen sondreo https github com sondreo b austnes kidneb7 https github com kidneb7 | os |
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manta-front-end | manta front end web app for interacting with manta network calamari network and dolphin testnet getting started for opensource development 1 clone the repo git clone git github com manta network manta front end git 2 change to the repo directory cd manta front end 3 install dependencies and start the dev server waiting for hmr working yarn yarn start 4 clone manta signer repo git clone git github com manta network manta signer git 5 change to the tauri ui directory cd manta signer ui src tauri 6 install tauri and build manta signer locally bash cargo install tauri cli cargo tauri build features unsafe disable cors 7 open the local disable cors version of manta signer by following guides https docs manta network docs guides mantasigner 8 follow guides https docs manta network docs guides dolphinpay and try mantapay on dolphin testnet 9 happy coding versioning the first digit of the version x in x y z refers to exceptional massive changes across manta front end other full stack repositories and the runtime such as the upgrade to testnet v2 reusable addresses major cryptographic changes the second digit of the version y in x y z refers to other changes that are coordinated across multiple full stack repositories and perhaps also the runtime for example an upgraded manta wasm wallet syncing protocol requiring changes to manta front end manta wasm wallet in sdk and the runtime would fall under this category the third digit of the version z in x y z refers to changes that only affect the front end a ui restyle would fall under this category | javascript front-end manta polkadot substrate | front_end |
nano-shell | nano shell omit in toc img src doc pic nano shell welcome png width 600 contents omit in toc hot key bind hot key bind add your command add your command how how example example configuring configuring readline configurations readline configurations command configurations command configurations shell configurations shell configurations shell io configurations shell io configurations porting nano shell to your project porting nano shell to your project nano shell is a light but powerful shell designed for embedded systems with or without an operating system main loop mode or react mode highly configurable powerful command line editing history record multi line input hot key bind etc memory friendly no malloc and free light build with arm none eabi gcc 7 3 1 20180622 o3 text sup 1 sup rodata bss sup 2 sup data main loop mode br all configurations on 2 5kb 1 03kb 852b 8b main loop mode br all configurations off sup 3 sup 616b 600b 180b 0b react mode br all configurations on 2 52kb 1 03kb 852b 8b react mode br all configurations off sup 3 sup 608b 600b 180b 0b 1 include built in help command 2 include input buffer default 128bytes and hisroty record buffer defaut 650bytes 5 128 2 3 except config shell cmd builtin help hot key bind nano shell has internally bound these hotkeys hot key ascii ansi escape code br xterm vt100 function ctrl a 1 home br move curosr to the start of line ctrl e 5 end br move curosr to the end of line ctrl p 16 up arrow br move cursor right one char ctrl n 14 down arrow br move cursor right one char ctrl b 2 left arrow br move cursor left one char ctrl f 6 right arrow br move cursor right one char ctrl d 4 delete br delete the character under the cursor ctrl k 11 erase forward br clears all characters from the cursor position to the end of the line ctrl u 21 erase backword br clears all characters from the cursor position to the start of the line ctrl c 3 kill the line home esc h move curosr to the beginning of line end esc f move curosr to the end of line up arrow esc a get the previous history down arrow esc b get the next history left arrow esc d left arrow br move cursor left one char right arrow esc c right arrow br move cursor right one char delete esc 3 delete the character under the cursor add your command how commands are added to nano shell by creating a new command structure this is done by first including command command h then using the nano shell add cmd macro to fill in a shell cmd t struct c nano shell add cmd name func brief help name name of the command note this is not a string func function pointer cmd const shell cmd t int int char const brief brief summaries of the command this is a string help detailed help information of the command this is a string commands with sub commands can easily be created with a combination of nano shell define subcmds nano shell subcmd entry and nano shell add cmd see examples for more details example 1 simple command c int do demo const shell cmd t pcmd int argc char const argv for int i 0 i argc i shell printf demo argv d s r n i argv i return 0 nano shell add cmd demo do demo a command demo it s detailed help information of demo command r n run demo in terminal img src doc pic command demo png width 600 run help and help demo in terminal img src doc pic help demo png width 600 example 2 command with sub commands it is possible to create commands with sub commands more nested command can also be created c create a bunch of commands to be run as a demo int top command fallback fct const shell cmd t pcmdt int argc char const argv if argc 1 shell printf s is not a subcommand of s r n argv 1 argv 0 else shell printf hey there is subcommands here type s help for more info r n argv 0 return 0 int do subcommand1 const shell cmd t pcmdt int argc char const argv shell puts this is sub command 1 r n return 0 int do subsubcommand1 const shell cmd t pcmdt int argc char const argv shell puts this is sub sub command 1 r n return 0 int do subsubcommand2 const shell cmd t pcmdt int argc char const argv shell puts this is sub sub command 2 r n return 0 sub sub commands group nano shell define subcmds subcommand2 group null nano shell subcmd entry subsubcommand1 do subsubcommand1 first sub sub command nano shell subcmd entry subsubcommand2 do subsubcommand2 second sub sub command sub commands group nano shell define subcmds top command group top command fallback fct nano shell subcmd entry subcommand1 do subcommand1 first subcommand nano shell subcmd entry subcommand2 nano shell subcmds fct subcommand2 group second subcommand with sub sub commands command with sub commands nano shell add cmd top command nano shell subcmds fct top command group a command with subcommand this command have 2 sub commands and one sub sub command r n in a terminal you get img src doc pic subcommand demo png width 600 configuring file shell config h shell config h readline configurations config shell input buffsize 127u default 127u config the command line input buffer size in byte config shell line editing default 1 enabled set this to 0 will disable command line editing config shell key seq bind default 1 enabled set this to 0 will disable ansi escape sequence nano shell will not be able to detect home end delete arrow keys doesn t affect ctrl p ctrl n etc config shell multi line default 1 enabled use backslash for line continuation when enabled set this to 0 will disable line continuation line continuation example br img src doc pic line continuation png width 600 br config shell hist min record default 5u set this to 0 will disable history record nano shell will take config shell hist min record 2 config shell input buffsize bytes to record at least config shell hist min record histroys the max history records depends on the average length of the input command configurations config shell cmd brief usage default 1 enabled command structure shell cmd t has a pointer point to brief usage information of the command set this to 0 will remove it config shell cmd long help default 1 enabled command structure shell cmd t has a pointer point to detailed help information of the command set this to 0 will remove it config shell cmd builtin help default 1 enabled nano shell provides a built in help command set this to 0 will remove the deault help command config shell cmd max argc default 10u config the max number of arguments must be no less than 1 shell configurations config shell prompt default nano shell config the shell promot that will displayed at the start of line if you don t need it set this to null or shell io configurations config shell printf buffer size default 128u config the buffer size of shell printf porting nano shell to your project 1 add nano shell root path to your project include path omit in toc 2 implement these functions file shell io h shell io shell io h in your project omit in toc this file may help shell io shell io c shell io shell io c c brief send a chararcter extern void shell putc char ch brief send string extern void shell puts const char str brief printf for nano shell extern int shell printf const char format attribute format printf 1 2 brief get next character available from stream param ch return the character in ch if there was return result is non zero if there was a character or 0 if there wasn t extern int shell getc char ch note int shell getc char ch is not used in react mode if you run nano shell in main loop mode to avoid losing characters you d better use a low layer receive fifo take uart for example you can detect incoming data using interrupts and then store each received character in a first in first out fifo buffer c void your uart interrupt handler void your uart receive code char ch uart get char store character in fifo fifo push ch then shell getc char ch may be c int shell getc char ch if fifo empty if no character in fifo return 0 return false ch fifo pop fifo is not empty get a character from fifo return 1 return true i write a simple and lock free fifo based on ring buffer in file shell io static fifo h shell io static fifo h maybe helpful 3 then modify the configuration file shell config h shell config h omit in toc 4 according to your system you can omit in toc 4 1 without os main loop mode omit in toc c include nano shell h int main void system init code nano shell infinite loop nano shell loop null 4 2 without os react mode non block omit in toc you can use it in interrupt take uart for example c void your uart interrupt handler void your uart receive code char ch uart get char nano shell isr interface nano shell react ch note nano shell react is non blocked unless there was an infinite loop in your command function you can call it when get a new character it is recommended to disable some configurations in shell config h if it was called in interrupt 4 3 with os take freertos for example omit in toc c include nano shell h int main void system init code create nano shell task taskhandle t shelltaskhandle null xtaskcreate nano shell loop shelltask stack size null task priority shelltaskhandle start rtos task scheduler vtaskstartscheduler note when determining the stack size for nano shell you should consider the memory occupied by commands added in nano shell 5 define nano shell section in your linker script file omit in toc add these 5 lines to your linker script file ld nano shell align 4 keep sort nano shell align 4 flash 6 build flash and try it omit in toc | os |
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machine_learning_project | application url housingpredictor https ml regression app herokuapp com start machine learning project software and account requirement 1 github account https github com 2 heroku account https dashboard heroku com login 3 vs code ide https code visualstudio com download 4 git cli https git scm com downloads 5 git documentation https git scm com docs gittutorial creating conda environment conda create p venv python 3 7 y conda activate venv or conda activate venv pip install r requirements txt to add files to git git add or git add file name note to ignore file or folder from git we can write name of file folder in gitignore file to check the git status git status to check all version maintained by git git log to create version commit all changes by git git commit m message to send version changes to github git push origin main to check remote url git remote v to setup ci cd pipeline in heroku we need 3 information 1 heroku email anishyadav7045075175 gmail com 2 heroku api key 3 heroku app name ml regression app build docker image docker build t image name tagname note image name for docker must be lowercase to list docker image docker images run docker image docker run p 5000 5000 e port 5000 f8c749e73678 to check running container in docker docker ps tos stop docker conatiner docker stop container id python setup py install install ipykernel pip install ipykernel data drift when your datset stats gets change we call it as data drift write a function to get training file path from artifact dir | ai |
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devops_labs | swagger generated server overview this server was generated by the swagger codegen https github com swagger api swagger codegen project by using the openapi spec https github com swagger api swagger core wiki from a remote server you can easily generate a server stub this is an example of building a swagger enabled flask server this example uses the connexion https github com zalando connexion library on top of flask requirements python 3 5 2 usage to run the server please execute the following from the root directory pip3 install r requirements txt python3 m swagger server and open your browser to here http localhost 8080 akifyuksel tutorial 1 0 0 ui your swagger definition lives here http localhost 8080 akifyuksel tutorial 1 0 0 swagger json to launch the integration tests use tox sudo pip install tox tox running with docker to run the server on a docker container please execute the following from the root directory bash building the image docker build t swagger server starting up a container docker run p 8080 8080 swagger server | cloud |
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HiBao | img src picture logo png alt logo style zoom 50 hibao h h hdmi h h h 1 taurus 2 openai api http 3 4 5 6 7 8 rgb h 9 hdmi taurus 1 98 90 2 2 1 5 3 4 gpt 3 5 5 5 rgb 1 openai api gpt 3 5 turbo 2 http pc mqtt pegasus 3 taurus yolo v2 fddb resnet 18 taurus 4 picture jpg pc workspace chagpt api call readme md pegasus workspace build gn readme md app demo picture png readme md raspiberry workspace 00 uart open sh 01 server open sh 02 iat open sh readme md rgb demo speaker demo iat demo uart demo taurus workspace readme md ai sample pc chatgpt http flask pegasus mqtt http taurus pegasus work pegasus c void thread main int arg void arg osthreadid t uart newthread thread uart uarttask 1 osthreadid t readtemp newthread thread readtemp dhttask 4 hi udelay 800000 hi udelay 800000 osstatus t status status osthreadterminate readtemp osthreadid t readred newthread thread readred adclighttask 3 osthreadid t report newthread thread report demoentry 2 thread1 infrared demo adc gpio 1 c static void adclighttask int arg void arg unsigned int ret 0 unsigned int data temp 0 int count 0 while num ret adcread iot adc channel 0 data temp iot adc equ model 4 iot adc cur bais default 0xff if ret iot success printf adc read fail r n return else vlt 1 8 4 4096 0 if data temp 1000 1 count 10 count else if count 10 count 0 data 0 0xaa data 1 0x55 data 2 0001 data 3 0xff printf red infrad taskmsleep 50 20 sleep 20ms thread2 dht11 demo dht11 dht11 gpio picture dht11 jpg c static void dhttask const int arg void arg printf dhttask start r n gpio dht11 init while num dht11 read data temp humi code printf temp d humi d r n temp humi dht11 read data thread3 uart connection mqtt c static void uarttask void uint32 t count 0 uint32 t len 0 unsigned char uartreadbuff uart buff size 0 ascii c ascii d uart1gpioinit uart1config while 1 uart1 send data through uart1 if count 50 data 2 0000 iotuartwrite hi uart idx 1 unsigned char data strlen data count else if count 50 data 0 0 data 1 0 data 2 0 data 3 0 count 0 uart1 receive data through uart1 len iotuartread hi uart idx 1 uartreadbuff uart buff size if len 0 uartreadbuff 0 printf uartreadbuff face uartreadbuff 3 usleep u sleep time void printhex const unsigned char data int len for int i 0 i len i printf 02x data i printf n thread4 mqtt client mqtt c publish sample hi void iotpublishsample void reported attribute wechatprofile wechatprofile subscribetype type status substate state status subreport reported status reportversion version status token clienttoken report motor reportaction subdeviceactionmotor motor reportaction motoractionstatus 0 0 motor off report temperature reportaction subdeviceactiontemperature temperature reportaction temperaturedata temp 30 temperature data report humidity reportaction subdeviceactionhumidity humidity reportaction humidityactiondata humidity humidity data reportaction subdeviceactiontestdata test reportaction testdata face 48 report light if g ligthstatus hi true wechatprofile reportaction subdeviceactionlight light wechatprofile reportaction lightactionstatus 1 1 light on else if g ligthstatus hi false wechatprofile reportaction subdeviceactionlight light wechatprofile reportaction lightactionstatus 0 0 light off else wechatprofile reportaction subdeviceactionlight light wechatprofile reportaction lightactionstatus 0 0 light off profile report iotprofilepropertyreport config user id wechatprofile taurus work 1 fddb 7000 2000 taurus 0 5 3000 2 fddb python darknet opencv 3 yolo v2 resnet 18 caffe 4 picture jpg 5 picture jpg taurus hdmi lcd c hi s32 yolo2handdetectresnetclassifycal uintptr t model video frame info s srcfrm video frame info s dstfrm sample svp nnie cfg s self sample svp nnie cfg s model hi s32 reslen 0 int objnum int ret int num 0 ret frmtoorigimg video frame info s srcfrm img sample check expr ret ret hi success ret hand detect for yuv frm to img fail ret x n ret objnum handdetectcal img objs send img to the detection net for reasoning for int i 0 i objnum i cnnboxs i objs i box rectbox box objs i box rectboxtran box hand frm width hand frm height dstfrm stvframe u32width dstfrm stvframe u32height sample prt yolo2 out d d d d n box xmin box ymin box xmax box ymax boxs i box biggestboxindex getbiggesthandindex boxs objnum sample prt biggestboxindex d objnum d n biggestboxindex objnum dstfrm when an object is detected a rectangle is drawn in the dstfrm if biggestboxindex 0 objboxs 0 boxs biggestboxindex mppfrmdrawrects dstfrm objboxs 1 rgb888 green draw retc thick target hand objnum is equal to 1 for int j 0 j objnum objnum 1 j if j biggestboxindex remainingboxs num boxs j objnum objnum 1 others hand objnum is equal to objnum 1 mppfrmdrawrects dstfrm remainingboxs objnum 1 rgb888 red draw retc thick the cropped image is preprocessed and sent to the classification network for inference ret imgyuvcrop img imgin cnnboxs biggestboxindex sample check expr ret ret 0 ret imgyuvcrop fail ret x n ret if imgin u32width width limit imgin u32height height limit compress mode e encompressmode srcfrm stvframe encompressmode ret origimgtofrm imgin frmin frmin stvframe encompressmode encompressmode sample prt crop u32width d img u32height d n imgin u32width imgin u32height ret mppfrmresize frmin frmdst image width image height ret frmtoorigimg frmdst imgdst ret cnncalimg self imgdst numinfo sizeof numinfo sizeof numinfo 0 reslen sample check expr ret ret 0 ret cnncalimg fail ret x n ret hi assert reslen sizeof numinfo sizeof numinfo 0 handdetectflag numinfo 0 mppfrmdestroy frmdst iveimgdestroy imgin else memcpy osdbuf unknown 10 hi osd attr s rgn txtrgninit rgn osdbuf txt begx txt begy argb1555 yellow2 font width and heigt use default 40 osdssetrgn g osdstrash g osd0trash rgn return ret pc work github christophezhao chagpt api call python calls chatgpt api multi turn dialogue support github com https github com christophezhao chagpt api call chatgpt chatgpt chatgpt python user dictionary unknown syp 30 yjq 30 h pgq 30 2023 h label to name unknown pgq yjq syp flask pc http flask pc python app route chatgpt methods post def chatgpt input text request form text print input input text if in input text or in input text requests post http 192 168 87 76 8999 getmessage data text return jsonify text finished 200 else response chat test input text keys model name request address context handler tokenizer print f nresponse response requests post http 192 168 87 76 8999 getmessage data text response return jsonify text response 200 app route changeuser methods post def changeuser input text request form text name label to name int input text print user name context handler clear user inform user dictionary get name user length tokenizer num tokens from string user inform context handler append cur to context user inform user length tag 2 return jsonify text change user successfully 200 if name main app run host 0 0 0 0 port 8999 raspiberry work rgb uart demo state infrared p t python if index 0 state state recongnize speech setreader speech reader type reader xuxiaobao speech setvolume 10 speech speech text speech encodingformat type gb2312 while speech getchipstatus speech chipstatus type chipstatus idle time sleep 0 1 open the recognition ser t2 write str encode cd userdata n time sleep 0 5 ser t2 write str encode myapp 1 n print open successful h python elif index 1 find hibao os system sudo pkill 9 f green breath py os system sudo pkill 9 f blue speak py os system sudo pkill 9 f change color py os system sudo pkill 9 f red spark py os system sudo python3 hibao project rgb demo set none py os popen bash hibao project rgb demo red spark sh speech setreader speech reader type reader xuxiaobao speech setvolume 10 speech speech text speech encodingformat type gb2312 while speech getchipstatus speech chipstatus type chipstatus idle time sleep 0 1 time sleep 1 python elif index 2 welcome back speech setreader speech reader type reader xuxiaobao speech setvolume 10 speech speech text speech encodingformat type gb2312 while speech getchipstatus speech chipstatus type chipstatus idle time sleep 0 1 state recongnize t pc t python ser t2 write str encode n ser t2 write str encode n ser t2 write str encode cd n print close successful s str index encode encoding utf 8 for i in range 20 ser p write s print requests post http 192 168 87 159 8999 changeuser data text str index json text speech setreader speech reader type reader xuxiaobao speech setvolume 10 speech speech text user dict str index speech encodingformat type gb2312 while speech getchipstatus speech chipstatus type chipstatus idle time sleep 0 1 state speak iat record python os system bash hibao project 02 iat open sh state state infrared os system sudo pkill 9 f green breath py os system sudo pkill 9 f blue speak py os system sudo pkill 9 f change color py os system sudo pkill 9 f red spark py os system sudo python3 hibao project rgb demo set none py os popen bash hibao project rgb demo change color sh w time sleep 20 rgb 1 pegasus 2 h 2 taurus 98 3 4 gpt pc api gpt 3 5 5 5 h 6 rgb h h 7 pegesus dht11 1 5 8 h http pc mqtt 1 h h 2 h 3 h 4 github todo 1 jain v learned miller e fddb a benchmark for face detection in unconstrained settings r umass amherst technical report 2010 2 taecharungroj v what can chatgpt do analyzing early reactions to the innovative ai chatbot on twitter big data and cognitive computing 2023 7 1 35 https doi org 10 3390 bdcc7010035 dht11 c void dht11 io out void gpio 11 iotgpiosetdir dht11 gpio iot gpio dir out dht11 1 dht11 0 uint8 t dht11 check void uint8 t retry 0 iotgpiovalue dht11 dq in dht11 io in set input while gpiogetinput dht11 gpio dht11 dq in retry 100 dht11 40 80us retry hi udelay 1 if retry 100 return uint8 t 1 else retry 0 while gpiogetinput dht11 gpio dht11 dq in retry 100 dht11 40 80us retry hi udelay 1 if retry 100 return uint8 t 1 return uint8 t 0 dht11 io dq dht11 1 0 uint8 t dht11 init void gpio iotgpioinit dht11 gpio gpio 11 gpio iosetfunc dht11 gpio iot io func gpio 11 gpio gpio 11 iotgpiosetdir dht11 gpio iot gpio dir out gpio 11 iotgpiosetoutputval dht11 gpio 1 dht11 rst return dht11 check dht11 dht11 void dht11 rst void dht11 io out set output dht11 dq out low dq hi udelay 20000 18ms dht11 dq out high dq 1 hi udelay 35 20 40us gpio int gpiogetinput iotioname id iotgpiovalue val iotgpiogetinputval id val return val void dht11 io in void iotgpiosetdir dht11 gpio iot gpio dir in iosetpull dht11 gpio iot io pull none c dht11 1 0 uint8 t dht11 read bit void uint8 t retry 0 iotgpiovalue dht11 dq in while gpiogetinput dht11 gpio dht11 dq in retry 100 retry hi udelay 1 retry 0 while gpiogetinput dht11 gpio dht11 dq in retry 100 retry hi udelay 1 hi udelay 40 40us 1 0 if gpiogetinput dht11 gpio dht11 dq in return 1 else return 0 dht11 uint8 t dht11 read byte void uint8 t i dat dat 0 for i 0 i 8 i dat 1 dat dht11 read bit return dat dht11 temp 0 50 humi 20 90 0 1 uint8 t dht11 read data uint8 t temp uint8 t humi uint8 t buf 5 0 uint8 t i dht11 rst if dht11 check 0 for i 0 i 5 i 40 buf i dht11 read byte if buf 0 buf 1 buf 2 buf 3 buf 4 humi buf 0 temp buf 2 else return 1 return 0 static void dhttask const int arg void arg printf dhttask start r n gpio uint8 t temp humi dht11 init while num dht11 read data temp humi code printf temp d humi d r n temp humi return null pc class context handler python class contexthandler object def init self max context 3200 context del config none super init self context self role lengths self max context max context the config of del context self context del config context del config def append cur to context self data complete length tag 0 if tag 0 role user elif tag 1 role assistant else role system role data role role content data self context append role data self role lengths append complete length def cut context self cur total length tokenizer if self context del config del context self context self role lengths cur total length self max context tokenizer tokenizer distance weights self context del config distance weights length weights self context del config length weights role weights self context del config role weights sys role ratio self context del config sys role ratio del ratio self context del config del ratio max keep turns self context del config max keep turns use the default pram else del context self context self role lengths cur total length self max context tokenizer tokenizer def clear self self context clear append cur to context 1 2 3 cut context class tokenizer python class tokennizer object def init self model name super init self encoding tiktoken encoding for model model name def num tokens from string self query string str int returns the number of tokens in a text string num tokens len self encoding encode query string return num tokens function del context python def del context dialogue context dialogue lengths cur total length max length tokenizer distance weights 0 05 length weights 0 4 role weights 1 sys role ratio 3 del ratio 0 4 max keep turns 30 dia nums len dialogue context if the dia nums exceeded max keep turns turns del the oldest dia sys role weights role weights sys role ratio is cut finished false while dia nums max keep turns index 0 while dialogue context index role system index 1 dialogue context pop index cur pop length dialogue lengths index dialogue lengths pop index cur total length cur pop length dia nums 1 if cur total length max length is cut finished true break if is cut finished return dialogue context dialogue lengths del score list for dia id in range dia nums distance dia nums dia id length dialogue lengths dia id content dialogue context dia id if content role assistant cal role weights sys role weights elif content role system cal role weights pre role weights else cal role weights role weights dia score distance distance weights length max length length weights cal role weights del score list append dia score del indexes argsort del score list reverse true del id 0 while cur total length max length if del id dia nums 1 raise exception the remain dialogue after context cutting still too long del dia dialogue context del indexes del id del dia length dialogue lengths del indexes del id exceed num cur total length max length delete the del ratio numbers at most for each dialogue ch del dia len len del dia content if exceed num del dia length del ratio 2 for token n del st index int exceed num del dia length ch del dia len 2 else del st index int del ratio ch del dia len deleted dia del dia content del st index deleted dia length tokenizer num tokens from string deleted dia cur total length del dia length deleted dia length dialogue context del indexes del id content deleted dia dialogue lengths del indexes del id deleted dia length del id 1 return dialogue context dialogue lengths 1 2 score distance times w distance frac length length max times w length times w calrole 3 user assistant system 1 3 10 chat python def chat test input s keys model name request address context handler tokenizer log time true context max 3200 requestor openai request keys model name request address if input s clear context handler clear print start a new session continue else inputs length tokenizer num tokens from string input s context handler append cur to context input s inputs length st time time time res requestor post request context handler context ed time time time response if res status code 200 response res json choices 0 message content cut n for show response response lstrip n completion length res json usage completion tokens total length res json usage total tokens context handler append cur to context response completion length tag 1 if total length context max context handler cut context total length tokenizer print context handler context else status code res status code reason res reason des res text raise print f visit error n status code status code n reason reason n err description des n f please check whether your account can access openai api normally if log time print f time cost ed time st time return response rgb include python from rpi ws281x import color led count 14 led led pin 18 di gpio18 led freq hz 800000 led signal frequency in hertz usually 800khz led dma 10 dma channel to use for generating signal try 10 led brightness 100 set to 0 for darkest and 255 for brightest led invert false true to invert the signal when using npn transistor level shift led channel 0 set to 1 for gpios 13 19 41 45 or 53 color setting red color 255 0 0 orange color 255 165 0 yellow color 255 255 0 green color 0 255 0 cyan color 0 255 255 bule color 0 0 255 purple color 225 0 225 white color 255 255 255 black color 0 0 0 gray color 128 128 128 brown color 165 42 42 change color python import colorsys import time import random from rpi ws281x import pixelstrip color from include import red 255 0 0 green 0 255 0 bule 0 0 255 duration 5 5 steps 50 50 create neopixel object with appropriate configuration strip pixelstrip led count led pin led freq hz led dma led invert led brightness led channel intialize the library must be called once before other functions strip begin print begin successful toggle all led light colors def change color color wait ms 40 for i in range strip numpixels strip setpixelcolor i color strip show time sleep wait ms 1000 0 def cycle light effect start color end color duration steps start hls colorsys rgb to hls start color end hls colorsys rgb to hls end color h increment end hls 0 start hls 0 steps interval duration steps for i in range steps h current h start hls 0 h increment i hls rgb current rgb colorsys hls to rgb current h start hls 1 start hls 2 current rgb round channel for channel in current rgb print print current rgb change color color current rgb 0 current rgb 1 current rgb 2 try while true cycle light effect red bule duration steps cycle light effect bule red duration steps except pass green breath python import time import random from rpi ws281x import pixelstrip color from include import create neopixel object with appropriate configuration strip pixelstrip led count led pin led freq hz led dma led invert led brightness led channel intialize the library must be called once before other functions strip begin print begin successful toggle all led light colors def change color color wait ms 20 for i in range strip numpixels strip setpixelcolor i color strip show time sleep wait ms 1000 0 setbrightness 0 255 0 255 def breathing color strip setbrightness 0 change color color strip show brightness 0 increment 1 while true brightness brightness increment strip setbrightness brightness strip show time sleep 0 005 if brightness 0 or brightness 255 increment increment try breathing green except pass blue speak python import time import random from rpi ws281x import pixelstrip color from include import create neopixel object with appropriate configuration strip pixelstrip led count led pin led freq hz led dma led invert led brightness led channel intialize the library must be called once before other functions strip begin print begin successful toggle all led light colors def change color color wait ms 20 for i in range strip numpixels strip setpixelcolor i color strip show time sleep wait ms 1000 0 setbrightness 0 255 0 255 def breathing color strip setbrightness 0 change color color strip show brightness 0 increment 1 while true brightness brightness increment strip setbrightness brightness strip show time sleep 0 002 if brightness 0 or brightness 255 increment increment try breathing cyan except pass red spark python import time import random from rpi ws281x import pixelstrip color from include import create neopixel object with appropriate configuration strip pixelstrip led count led pin led freq hz led dma led invert led brightness led channel intialize the library must be called once before other functions strip begin print begin successful toggle all led light colors def change color color wait ms 20 for i in range strip numpixels strip setpixelcolor i color strip show time sleep wait ms 1000 0 setbrightness 0 255 0 255 def breathing color strip setbrightness 0 change color color strip show brightness 0 increment 1 count 0 while true brightness brightness increment strip setbrightness brightness strip show time sleep 0 001 if brightness 0 or brightness 255 increment increment count count 1 if count 7 change color color 0 0 0 break try breathing red except pass python from flask import flask request jsonify import sys import os sys path append from speech import speech import time import smbus speech speech speech setreader speech reader type reader xuxiaobao speech setvolume 10 speech speech text speech encodingformat type gb2312 while speech getchipstatus speech chipstatus type chipstatus idle time sleep 0 1 app flask name app route getmessage methods post def chatgpt input request form text print input response message successfully os system sudo pkill 9 f green breath py os system sudo pkill 9 f red spark py os system sudo pkill 9 f change color py os system sudo python3 hibao project rgb demo set none py os popen hibao project rgb demo blue speak sh speech setreader speech reader type reader xuxiaobao speech setvolume 10 speech speech text input speech encodingformat type gb2312 while speech getchipstatus speech chipstatus type chipstatus idle time sleep 0 1 if input os system sudo pkill 9 f iat return jsonify response 200 if name main app run host 0 0 0 0 port 8999 c ifly auto transform include stdlib h include stdio h include string h include unistd h include curl curl h include cjson cjson h include qisr h include msp cmn h include msp errors h include speech recognizer h define frame len 640 define buffer size 4096 upload user words static int upload userwords char userwords null size t len 0 size t read len 0 file fp null int ret 1 fp fopen userwords txt rb if null fp printf nopen userwords txt failed n goto upload exit fseek fp 0 seek end len ftell fp fseek fp 0 seek set userwords char malloc len 1 if null userwords printf nout of memory n goto upload exit read len fread void userwords 1 len fp if read len len printf nread userwords txt failed n goto upload exit userwords len 0 mspuploaddata userwords userwords len sub uup dtt userword ret if msp success ret printf nmspuploaddata failed errorcode d n ret goto upload exit upload exit if null fp fclose fp fp null if null userwords free userwords userwords null return ret static void show result char string char is over printf rresult s string if is over putchar n static char g result null static unsigned int g buffersize buffer size void on result const char result char is last if result size t left g buffersize 1 strlen g result size t size strlen result if left size g result char realloc g result g buffersize buffer size if g result g buffersize buffer size else printf mem alloc failed n return strncat g result result size show result g result is last if is last if strlen g result 0 send chat nulltoken else send chat g result static size t a size 0 size t write callback char ptr size t size size t nmemb void userdata size t realsize size nmemb char result char userdata memcpy result ptr realsize result realsize 0 printf n s n result return realsize static curl curl null void send chat const char string curlcode res char data 1024 size t size strlen string prtntf ld size sprintf data text s string printf n s n data char result 1024 curl curl easy init if curl curl easy setopt curl curlopt url http 192 168 87 159 8999 chatgpt curl easy setopt curl curlopt postfields data curl easy setopt curl curlopt writefunction write callback curl easy setopt curl curlopt writedata result printf result s n result res curl easy perform curl if res curle ok fprintf stderr curl easy perform failed s n curl easy strerror res printf result n s n result json cjson root cjson parse result if root printf error before s n cjson geterrorptr return printf root s n root cjson answer cjson getobjectitemcasesensitive root text if cjson isstring answer answer valuestring null printf answer s n answer valuestring a size strlen answer valuestring printf length of answer d n a size cjson delete root curl easy cleanup curl void on speech begin if g result free g result g result char malloc buffer size g buffersize buffer size memset g result 0 g buffersize printf start listening n void on speech end int reason if reason end reason vad detect printf nspeaking done n else printf nrecognizer error d n reason demo send audio data from a file static void demo file const char audio file const char session begin params int errcode 0 file f pcm null char p pcm null unsigned long pcm count 0 unsigned long pcm size 0 unsigned long read size 0 struct speech rec iat struct speech rec notifier recnotifier on result on speech begin on speech end if null audio file goto iat exit f pcm fopen audio file rb if null f pcm printf nopen s failed n audio file goto iat exit fseek f pcm 0 seek end pcm size ftell f pcm fseek f pcm 0 seek set p pcm char malloc pcm size if null p pcm printf nout of memory n goto iat exit read size fread void p pcm 1 pcm size f pcm if read size pcm size printf nread s error n audio file goto iat exit errcode sr init iat session begin params sr user recnotifier if errcode printf speech recognizer init failed d n errcode goto iat exit errcode sr start listening iat if errcode printf nsr start listening failed error code d n errcode goto iat exit while 1 unsigned int len 10 frame len 200ms audio int ret 0 if pcm size 2 len len pcm size if len 0 break ret sr write audio data iat p pcm pcm count len if 0 ret printf nwrite audio data failed error code d n ret goto iat exit pcm count long len pcm size long len errcode sr stop listening iat if errcode printf nsr stop listening failed error code d n errcode goto iat exit iat exit if null f pcm fclose f pcm f pcm null if null p pcm free p pcm p pcm null sr stop listening iat sr uninit iat demo recognize the audio from microphone static void demo mic const char session begin params int errcode int i 0 struct speech rec iat struct speech rec notifier recnotifier on result on speech begin on speech end errcode sr init iat session begin params sr mic recnotifier if errcode printf speech recognizer init failed n return errcode sr start listening iat if errcode printf start listen failed d n errcode demo 15 seconds recording while i 15 sleep 1 errcode sr stop listening iat if errcode printf stop listening failed d n errcode sr uninit iat main thread start stop record query the result of recgonization record thread record callback data write helper thread ui keystroke detection int main int argc char argv curl global init curl global all int ret msp success int upload on 1 whether upload the user word login params please do keep the appid correct const char login params appid cdd053ec work dir int aud src 0 from mic or file see iflytek msc reference manual const char session begin params sub iat domain iat language zh cn accent mandarin sample rate 16000 result type plain result encoding utf8 login first the 1st arg is username the 2nd arg is password just set them as null the 3rd arg is login paramertes ret msplogin null null login params if msp success ret printf msplogin failed error code d n ret goto exit login fail exit the program printf want to upload the user words n0 no n1 yes n scanf d upload on if 0 printf uploading the user words n ret upload userwords if msp success ret goto exit printf uploaded successfully n baprintf where the audio comes from n 0 from a audio file n1 from microphone n scanf d aud src if 1 printf demo recognizing the speech from microphone n printf speak in 15 seconds n while 1 system sudo pkill 9 f blue speak py system sudo pkill 9 f change color py system sudo pkill 9 f green breath sh system sudo python3 hibao project rgb demo set none py popen hibao project rgb demo green breath sh w demo mic session begin params for int i 0 i 15 i printf d n i sleep 1 printf test d n a size if a size 0 int k a size 9 10 if k 0 while k sleep 1 k printf d n k a size 0 printf time passed n else printf demo recgonizing the speech from a recorded audio file n demo file wav iflytek02 wav session begin params exit curl global cleanup msplogout logout return 0 | os |
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ESD | esd embedded system design this repository is the code base of projects given in ece 561 embedded system design course | os |
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QEMU_lm3s6965evb | qemu lm3s6965evb this project uses qemu https www qemu org to emulate an arm based systems called lm3s6965 more information on this device can be found on the texas instruments website https www ti com product lm3s6965 this is a cortex m3 based chip arm v7 m architecture that has an mpu note this project is based on a linux machine like ubuntu if you want to run it on windows a virtual machine can be used to follow the steps to start you can clone this project using the following command git clone recurse submodules https github com introduction to system on chip qemu lm3s6965evb git it will create a folder called qemu lm3s6965evb prerequisites it is necessary to have build essential make and git sudo apt y install git make build essential cmsis during the clone of the project cmsis is already downloaded and configured to be built in the makefile of the project the path to cmsis in the makefile is stored in variable cmsis install qemu before compiling and running programs you need to install qemu either using apt from ubuntu sudo apt y install qemu system arm or by building it from source note you might need to install additional dependencies and the compilation might take a while cd qemu configure make j4 qemu path to the qemu arm system is configured in the makefile through the variable qemu path get the arm cortex m toolchain this project will cross compile a c application from an intel processor like most laptop desktop running on a x86 or x86 64 architecture to an arm v7m core the toolchain can be found on arm website https developer arm com tools and software open source software developer tools gnu toolchain gnu rm downloads the version used for this project is gcc arm none eabi 9 2019 q4 major wget https developer arm com media files downloads gnu rm 9 2019q4 gcc arm none eabi 9 2019 q4 major x86 64 linux tar bz2 tar xvf gcc arm none eabi 9 2019 q4 major x86 64 linux tar bz2 the makefile is also configured to get this toolchain through the variable toolchain compile and run the project the makefile is gathering all the compilation flags source files and includes to compile the final binary the command to be used is make which should output something like make build the assembly startup file first assembly code line called when the processor starts this generates the boot o binary file gcc arm none eabi 9 2019 q4 major bin arm none eabi gcc mcpu cortex m3 specs nano specs specs nosys specs specs rdimon specs wall g3 i cmsis 5 device arm armcm3 include i cmsis 5 cmsis core include i mthumb nostartfiles c cmsis 5 device arm armcm3 source gcc startup armcm3 s o boot o compile the c file and link the boot o binary the linker script gcc arm ld is used by the linker to know where to put the different sections of the program and at which address this line creates the cm3 elf program gcc arm none eabi 9 2019 q4 major bin arm none eabi gcc cmsis 5 device arm armcm3 source system armcm3 c start c main c boot o mcpu cortex m3 specs nano specs specs nosys specs specs rdimon specs wall g3 i cmsis 5 device arm armcm3 include i cmsis 5 cmsis core include i mthumb nostartfiles t gcc arm ld o cm3 elf dumps the content of the produced elf into the file objdump cm3 elf can be used for inspection of the code and to analyse the assembly code produced and the addresses of the functions gcc arm none eabi 9 2019 q4 major bin arm none eabi objdump d cm3 elf objdump cm3 elf now that the program is build it can either be run or debugged note the flag g3 indicating that some symbols are put in the final binary to help the debug process debug the project this can be done in two steps start qemu with the binary and request a gdbserver in one terminal make gdbserver qemu system arm machine lm3s6965evb cpu cortex m3 m 4096 nographic semihosting device loader file cm3 elf machine accel tcg s s d int cpu reset cpu reset cpu 0 r00 00000000 r01 00000000 r02 00000000 r03 00000000 r04 00000000 r05 00000000 r06 00000000 r07 00000000 r08 00000000 r09 00000000 r10 00000000 r11 00000000 r12 00000000 r13 00000000 r14 00000000 r15 00000000 xpsr 40000000 z a priv thread cpu reset cpu 0 r00 00000000 r01 00000000 r02 00000000 r03 00000000 r04 00000000 r05 00000000 r06 00000000 r07 00000000 r08 00000000 r09 00000000 r10 00000000 r11 00000000 r12 00000000 r13 00000000 r14 ffffffff r15 00000000 xpsr 40000000 z a priv thread a useful aspect of qemu is that it can print logs when a process catches an exception it indicates the logs that will be printed if a violation is detected taking exception 4 data abort with cfsr daccviol and mmfar 0x20010000 exception taken from a data violation this means the program is inside the memmanage handler in the makefile you can add d int cpu reset to print those traces from qemu open another terminal and run gdb with the gdbserver as target make gdb gcc arm none eabi 9 2019 q4 major bin arm none eabi gdb cm3 elf ex target remote 1234 gnu gdb gnu tools for arm embedded processors 9 2019 q4 major 8 3 0 20190709 git copyright c 2019 free software foundation inc license gplv3 gnu gpl version 3 or later http gnu org licenses gpl html this is free software you are free to change and redistribute it there is no warranty to the extent permitted by law type show copying and show warranty for details this gdb was configured as host x86 64 linux gnu target arm none eabi type show configuration for configuration details for bug reporting instructions please see http www gnu org software gdb bugs find the gdb manual and other documentation resources online at http www gnu org software gdb documentation for help type help type apropos word to search for commands related to word reading symbols from cm3 elf remote debugging using 1234 reset handler at cmsis 5 device arm armcm3 source gcc startup armcm3 s 78 78 bl systeminit gdb now typical gdb commands step next continue break can be used to debug the program pressing ctrl x a it is possible to need the source file with the line being debugged in highlight run if debug is not necessary simply use make run and the program will execute and stop | qemu arm makefile cmsis lm3s6965evb mpu rtos | os |
nuclide | nuclide circle status https circleci com gh facebook nuclide tree master svg style shield circle token a805ec51c07ae99799ce548795383dd1f1e4dc76 https circleci com gh facebook nuclide nuclide http nuclide io is a collection of features for atom https atom io to provide ide like functionality for a variety of programming languages and technologies the nuclide license https github com facebook nuclide blob master license has certain limitations around distribution and should not be considered an open source license https opensource org licenses alphabetical however this does not affect your ability to fork the project and make contributions https github com facebook nuclide blob master contributing md documentation the full documentation http nuclide io docs for nuclide provides information for client installation http nuclide io docs editor setup mac http nuclide io docs editor setup mac linux http nuclide io docs editor setup linux windows is not supported http nuclide io docs editor setup windows server installation http nuclide io docs editor setup installing nuclide server getting started feature walkthrough http nuclide io docs quick start getting started building from source http nuclide io docs advanced topics building from source | front_end |
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trankit | h2 align center trankit a light weight transformer based python toolkit for multilingual natural language processing h2 div align center a href https github com nlp uoregon trankit blob master license img alt github src https img shields io github license nlp uoregon trankit svg color blue a a href https trankit readthedocs io en latest badge latest img src https readthedocs org projects trankit badge version latest alt documentation status a a href http nlp uoregon edu trankit img alt demo website src https img shields io website http trankit readthedocs io en latest index html svg down color red down message offline up message online a a href https pypi org project trankit img alt pypi version src https img shields io pypi v trankit color blue a a href https pypi org project trankit img alt python versions src https img shields io pypi pyversions trankit colorb blue a div our technical paper https arxiv org pdf 2101 03289 pdf for trankit won the outstanding demo paper award at eacl 2021 https 2021 eacl org please cite the paper if you use trankit in your research bibtex inproceedings nguyen2021trankit title trankit a light weight transformer based toolkit for multilingual natural language processing author nguyen minh van and lai viet dac and veyseh amir pouran ben and nguyen thien huu booktitle proceedings of the 16th conference of the european chapter of the association for computational linguistics system demonstrations year 2021 boom boom boom trankit v1 0 0 is out 90 new pretrained transformer based pipelines for 56 languages the new pipelines are trained with xlm roberta large which further boosts the performance significantly over 90 treebanks of the universal dependencies v2 5 corpus check out the new performance here https trankit readthedocs io en latest performance html this page https trankit readthedocs io en latest news html trankit large shows you how to use the new pipelines auto mode for multilingual pipelines in the auto mode the language of the input will be automatically detected enabling the multilingual pipelines to process the input without specifying its language check out how to turn on the auto mode here https trankit readthedocs io en latest news html auto mode for multilingual pipelines thank you loretoparisi https github com loretoparisi for your suggestion on this command line interface is now available to use this helps users who are not familiar with python programming language use trankit easily check out the tutorials on this page https trankit readthedocs io en latest commandline html trankit is a light weight transformer based python toolkit for multilingual natural language processing nlp it provides a trainable pipeline for fundamental nlp tasks over 100 languages https trankit readthedocs io en latest pkgnames html trainable languages and 90 downloadable https trankit readthedocs io en latest pkgnames html pretrained languages their code names pretrained pipelines for 56 languages https trankit readthedocs io en latest pkgnames html pretrained languages their code names div align center img src https raw githubusercontent com nlp uoregon trankit master docs source architecture jpg height 300px div trankit outperforms the current state of the art multilingual toolkit stanza stanfordnlp in many tasks over 90 universal dependencies v2 5 treebanks of 56 different languages https trankit readthedocs io en latest performance html universal dependencies v2 5 while still being efficient in memory usage and speed making it usable for general users in particular for english trankit is significantly better than stanza on sentence segmentation 9 36 and dependency parsing 5 07 for uas and 5 81 for las for arabic our toolkit substantially improves sentence segmentation performance by 16 36 while chinese observes 14 50 and 15 00 improvement of uas and las for dependency parsing detailed comparison between trankit stanza and other popular nlp toolkits i e spacy udpipe in other languages can be found here https trankit readthedocs io en latest performance html universal dependencies v2 5 on our documentation page https trankit readthedocs io en latest index html we also created a demo website for trankit which is hosted at http nlp uoregon edu trankit installation trankit can be easily installed via one of the following methods using pip pip install trankit the command would install trankit and all dependent packages automatically from source git clone https github com nlp uoregon trankit git cd trankit pip install e this would first clone our github repo and install trankit fixing the compatibility issue of trankit with transformers previous versions of trankit have encountered the compatibility issue https github com nlp uoregon trankit issues 5 when using recent versions of transformers https github com huggingface transformers to fix this issue please install the new version of trankit as follows pip install trankit 1 1 0 if you encounter any other problem with the installation please raise an issue here https github com nlp uoregon trankit issues new to let us know thanks usage trankit can process inputs which are untokenized raw or pretokenized strings at both sentence and document level currently trankit supports the following tasks sentence segmentation tokenization multi word token expansion part of speech tagging morphological feature tagging dependency parsing named entity recognition initialize a pretrained pipeline the following code shows how to initialize a pretrained pipeline for english it is instructed to run on gpu automatically download pretrained models and store them to the specified cache directory trankit will not download pretrained models if they already exist python from trankit import pipeline initialize a multilingual pipeline p pipeline lang english gpu true cache dir cache perform all tasks on the input after initializing a pretrained pipeline it can be used to process the input on all tasks as shown below if the input is a sentence the tag is sent must be set to true python from trankit import pipeline p pipeline lang english gpu true cache dir cache document level processing untokenized doc hello this is trankit pretokenized doc hello this is trankit perform all tasks on the input processed doc1 p untokenized doc processed doc2 p pretokenized doc sentence level processing untokenized sent this is trankit pretokenized sent this is trankit perform all tasks on the input processed sent1 p untokenized sent is sent true processed sent2 p pretokenized sent is sent true note that although pretokenized inputs can always be processed using pretokenized inputs for languages that require multi word token expansion such as arabic or french might not be the correct way please check out the column requires mwt expansion of this table https trankit readthedocs io en latest pkgnames html pretrained languages their code names to see if a particular language requires multi word token expansion or not for more detailed examples please check out our documentation page https trankit readthedocs io en latest overview html multilingual usage starting from version v1 0 0 trankit supports a handy auto mode https trankit readthedocs io en latest news html auto mode for multilingual pipelines in which users do not have to set a particular language active before processing the input in the auto mode trankit will automatically detect the language of the input and use the corresponding language specific models thus avoiding switching back and forth between languages in a multilingual pipeline python from trankit import pipeline p pipeline auto tokenizing an english input en output p tokenize i figured i would put it out there anyways pos morphological tagging and dependency parsing a french input fr output p posdep on pourra toujours parler propos d averro s de d centrement du sujet ner tagging a vietnamese input vi output p ner cu c ti m th nghi m ti n h nh t i h c vi n qu n y h n i in this example the code name auto is used to initialize a multilingual pipeline in the auto mode for more information please visit this page https trankit readthedocs io en latest news html auto mode for multilingual pipelines note that besides the new auto mode the manual mode https trankit readthedocs io en latest overview html multilingual usage can still be used as before building a customized pipeline training customized pipelines is easy with trankit via the class tpipeline below we show how we can train a token and sentence splitter on customized data python from trankit import tpipeline tp tpipeline training config task tokenize save dir saved model train txt fpath train txt train conllu fpath train conllu dev txt fpath dev txt dev conllu fpath dev conllu trainer train detailed guidelines for training and loading a customized pipeline can be found here https trankit readthedocs io en latest training html sharing your customized pipelines in case you want to share your customized pipelines with other users please create an issue here https github com nlp uoregon trankit issues new and provide us the following information training data that you used to train your models e g data license data source and some data statistics i e sizes of training development and test data performance of your pipelines on your test data using the official evaluation script https universaldependencies org conll18 evaluation html a downloadable link to your trained model files a google drive link would be great after we receive your request we will check and test your pipelines once everything is done we would make the pipelines accessible by other users via new language codes acknowledgements this project has been supported by the office of the director of national intelligence odni intelligence advanced research projects activity iarpa via iarpa contract no 2019 19051600006 under the better extraction from text towards enhanced retrieval better program https www iarpa gov index php research programs better we use xlm roberta https arxiv org abs 1911 02116 and adapters https arxiv org abs 2005 00247 as our shared multilingual encoder for different tasks and languages the adapterhub https github com adapter hub adapter transformers is used to implement our plug and play mechanism with adapters to speed up the development process the implementations for the mwt expander and the lemmatizer are adapted from stanza https github com stanfordnlp stanza to implement the language detection module we leverage the langid https github com saffsd langid py library | nlp natural-language-processing pytorch language-model xlm-roberta machine-learning deeplearning artificial-intelligence universal-dependencies multilingual adapters sentence-segmentation tokenization part-of-speech-tagging morphological-tagging dependency-parsing lemmatization | ai |
nlp | what is this repository for nlp trie huffman coding machine learning similarity | ai |
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ng-best-practices | this project is aimed to be the support example of a tutorial https github com haythem ouederni ng best practices issues 1 walking you through best practices of front end development web mobile with a concrete example based on an angular https angular io project to see tutorial come as soon as possible you can vote here https github com haythem ouederni ng best practices issues 1 introduction this project is the result of my experience working on helping startups and more traditional industries in finance and aerospatial defining and developing their front end projects web and mobule i have noticed that every time one of the most difficult parts when launching a product is defining the best practices and finding the best tools to put in place the development workflow so i have decided to create this project to be a concentrate of best practices ready to use out of the box and that may save developers and spetially tech leads technical architects days and even months of hard work to find and define the best workflow for their projects this project tutorial main focus is development best practices so for the beginning it won t include any material related to continuous integration https fr atlassian com continuous delivery continuous integration or application deployment notice 1 many of the best practices present in this project are as mentioned before general to front end development and even to development in general not only front end so even if you are not using angular in your project you can walk through it to get some interesting ideas notice 2 you can see the content of different project commits to have an idea of the evolution of the project and the steps to add include a specific tool library or pattern to the project angular best practices example project this project was generated with angular cli https github com angular angular cli version 7 3 1 for this project i mainly use yarn https yarnpkg com but you can run the same scripts commands using npm https www npmjs com for example to start the project using yarn you run yarn start to do the same thing using npm you can run npm run start before you start prerequisites to be able to launch this project you need to install node js https nodejs org mandatory npm https www npmjs com it can be installed with nodejs mandatory yarn https yarnpkg com if you want to use is instead of npm to run different scripts optional the ide or code editor of you choice i can suggest you the use of vs code https code visualstudio com which is free and very practical for front end development and comes with many helpful plugins you may also want to use webstorm https www jetbrains com webstorm which is not free at the same time you have a free 30 day trial to test it there is an other option which is atom https atom io so it is up to you to choose which tool suits you most before being able to start the project you have to install the different dependencies libraries to do so run script if npm npm install if yarn yarn optional tools here is a list of optional tools you may need in general for your projects development git https git scm com for source control and be able to share code with other co workers or just store your code and have access to the history of your project evolution sourcetree https www sourcetreeapp com a very user friendly and visual tool to handle your source control git branches the main branch where you can find the latest working and tested code is the master https github com haythem ouederni ng best practices you can follow the day to day commits and development on the develop https github com haythem ouederni ng best practices tree develop branch a tagging system will come along different upgrades and releases of the project development server run yarn start for a dev server navigate to http localhost 4200 the app will automatically reload if you change any of the source files code scaffolding run ng generate component component name to generate a new component you can also use ng generate directive pipe service class guard interface enum module build run yarn build to build the project the build artifacts will be stored in the dist directory use the prod flag for a production build running unit tests actually a default angular cli https cli angular io generated project uses karma https karma runner github io latest index html tool for unit testing the problem with karma it can be an advantage in some cases is that it needs to launch a browser to run a test which in many cases is not necessary and at the same time extends the test execution time in addition you may have continuous integration integrated to you development delivery process that runs on an environment where you can have a browser there is an interesting alternative to karma which is jest https jestjs io it makes it faster and easier to write tests no browser is needed it comes with built in mocking and assertion abilities in addition jest runs your tests concurrently in parallel providing a smoother faster test run jest preset angular https github com thymikee jest preset angular used to make the jest configuration easier the actual used version is 6 0 2 so documentation and the configuration will be different for the futur versions of this library run yarn test all to execute the unit tests via jest on the whole project if you want to run unit tests in a specific project like the connection project run yarn test connection don t forget to add the needed script to your package json file in addiion to the matching jest configuration file to be able to launch test on a new library you can take the example of how it is done for the connection library you can also launch you tests and watch for changes by running for exmaple yarn test all watch vs code and jest debug if you use vs code https code visualstudio com you can debug your jest based unit tests by adding a launch json file under your vscode folder you can find an example file in the actual repo the debugger will use the built in node debugger a more complete documentation can be fond here https github com microsoft vscode recipes tree master debugging jest tests running end to end tests run yarn e2e to execute the end to end tests via protractor http www protractortest org imports if we want to import a component from connection library we can use the connection annotation example import connectionmodule from connection this is possible thanks to the adding of the paths attribute to the tsconfig json file json compileroptions paths connection projects connection src public api if we want to get more specific about the path for example in case of a circular dependancy we can add an other path to the tsconfig json file like follow json compileroptions paths connection projects connection src public api connection projects connection src it will allow as to import components or other angular exported functionalities like the following example example import connectioncomponent from connection lib modules main pages git to make sure that developers follow a precise worklow while commiting and pushing the code so that you don t have to do verfications and run scripts manually the following tools are very useful cz cli https github com commitizen cz cli when you commit with commitizen you ll be prompted to fill out any required commit fields at commit time in package json you add json scripts commit git cz so when you run yarn commit the cz cli is used so no more direct git commit cz customizable https github com leonardoanalista cz customizable the customizable commitizen plugin to help achieve consistent commit messages like the angularjs team it comes to complete the cz cli plugin in package json you add json config commitizen path node modules cz customizable cz customizable config path to custom cz config js if you don t give any custom file in the configuration config cz customizable config the cz config js file present at the root of the project will be used note to be able to use vs code https code visualstudio com to edit git commit comments or other file manipulation tasks instead of default vim you can run git config global core editor code wait at the condiction that vs code is available from commande line you can check it by running code help more information here https stackoverflow com questions 30024353 how to use visual studio code as default editor for git husky https github com typicode husky to easily edit git hooks add the husky configuration at the root of the package json file json husky hooks pre commit yarn lintstaged prepush yarn prod if you want to skip the hools just add the no verify flag to your git command example git push no verify commitlint cli https github com conventional changelog commitlint as its name incdicates this tool gives you the possibility to add an other check on the commit messages and if the meet the conventional commit format https www conventionalcommits org en v1 0 0 beta 3 or the conventions you have defined yourself so to the already defined husky hooks configuration you can add the commit msg hook json husky hooks commit msg commitlint e husky git params commit msg hook allows you to lint commits before they are created you can add a commitlint config js file at the root of the project to define linting rules conventions commitlint config js example javascript module exports we use the default commitlint config conventional rules you have to install commitlint config conventional library to be able to use it extends commitlint config conventional any rules defined here will override rules from commitlint config conventional custom rules rules header max length 2 always 100 subject case 2 never sentence case start case pascal case upper case note if you want to retry a commit so that you don t have to re enter the same information again just run yarn commit retry routing the angular s routermodule https angular io api router routermodule was used the angular s documentation https angular io tutorial toh pt5 is very complete and i advise you to take a look at it in this project i have made the choice that for the app standalone project s i use the direct routing loading in the other hand for the main app root app the module are lazy loaded and it affects the way the routing works to see how how the lzay loading is dealt with you can take a look at the src app lazy directory where the lazy loaded modules are defined then these modules are really lazy loaded within the src app app routing module ts file for each lazy loaded module a path is defined this path must preceed all the paths defined in the original module exemple suppose that in your orignal module you access the page one content via the url localhost 4200 page one when you direct load it like in the app standalone project at the same time the path you have defined to lazy load the same module is my lazy loaded path so to access the same content page you should use the url localhost 4200 my lazy loaded path page one instead and here to make my module work while lazy loaded or direct loaded a combination of forroot method over the loaded module and environment variables is used reactive forms when it comes to manipulating forms in angular you have the choice between reactive forms https angular io guide reactive forms and template driven forms https angular io guide forms in the official angular documentation https angular io guide forms overview you can find reactive forms are more robust they re more scalable reusable and testable if forms are a key part of your application or you re already using reactive patterns for building your application use reactive forms template driven forms are useful for adding a simple form to an app such as an email list signup form they re easy to add to an app but they don t scale as well as reactive forms if you have very basic form requirements and logic that can be managed solely in the template use template driven forms you can find a table of key differences here https angular io guide forms overview key differences for this project i have chosen to use reactive forms https angular io guide reactive forms for all the advantages it comes with like having a strcutered data model or taking advantage of synchronicity between your template view html and you controller component class model besides generally in big projects you may have complex forms and the reactive forms makes the task build them easier for you styling bootstrap when you launch your project you can base it first on an already existing styling library it helps you save time when styling your application here are some examples of libraries you can use bootstrap https getbootstrap com it is not specific to angular you can use whatever framework you use and to make using it easier in angular projects you may use ng bootstrap https ng bootstrap github io home library angular material https material angular io angular specific gives acces to material deisgn components for angular zurb foundation https foundation zurb com examples of foundation components for sites here https foundation zurb com sites docs kitchen sink html material https material io develop web components animation actually for this project it is bootstrap which was used not ng boostrap ngxs and facade pattern ngxs most libraries like react angular etc are built with a way for components to internally manage their state without any need for an external library or tool it does well for applications with few components but as the application grows bigger managing states shared across components becomes a chore in an app where data is shared among components it might be confusing to actually know where a state should live ideally the data in a component should live in just one component so sharing data among sibling components becomes difficult source https blog logrocket com why use redux reasons with clear examples d21bffd5835 the way a state management library works is simple there is a central store that holds the entire state of the application each component can access the stored state without having to send down props from one component to another for example for react https reactjs org one of the most used state management libraries is redux https redux js org and the use of the react redux https github com reduxjs react redux package makes it easier for sure you have other state management libraries for react like facebook s flux https github com facebook flux so choose what suits you most knwoing that redux is more used that flux because it is not centred on react and can be used with any other view library for angular you have many options for state management like ngxs https github com ngxs store ngxs is a state management pattern library for angular it acts as a single source of truth for your application s state providing simple rules for predictable state mutations ngrx https ngrx io store is rxjs powered state management for angular applications inspired by redux store is a controlled state container designed to help write performant consistent applications on top of angular datorama akita https github com datorama akita akita is a state management pattern built on top of rxjs which takes the idea of multiple data stores from flux and the immutable updates from redux along with the concept of streaming data to create the observable data store model for angular after studying the different options i find that ngxs is the best option it is written for angular at the first place so it is implemented following the angular s code style and takes andvantage of the dependency injection provided by angular in addition it is less verbose then other libraries for these reasons we have made the choice to use it in many companies i worked with you can find here https medium com amcdnl why another state management framework for angular b4b4c19ef664 of a complete explanation of why to use ngxs used ngxs plugins for this repo logger https ngxs gitbook io ngxs plugins logger a simple console log plugin to log actions as they are processed devtools https ngxs gitbook io ngxs plugins devtools plugin with integration with the redux devtools extension http extension remotedev io router https ngxs gitbook io ngxs plugins router to help you handle navigation facade pattern the facade pattern is a software design pattern https en wikipedia org wiki software design pattern commonly used in object oriented programming https en wikipedia org wiki object oriented programming analogous to a facade https en wikipedia org wiki facade in architecture a facade is an object that serves as a front facing interface masking more complex underlying or structural code a facade can improve the readability and usability of a software library by masking interaction with more complex components behind a single and often simplified api provide a context specific interface to more generic functionality complete with context specific input validation serve as a launching point for a broader refactor of monolithic or tightly coupled systems in favor of more loosely coupled code while this seems like a rather trivial change and an extra layer the facade has a huge positive impact of developer productivity and yields significantly less complexity in the view layers source https medium com ngxs ngxs facade 3aa90c41497b an other advantage is that it makes your controllers angular components for example independant from the state management library you have chosen to use internationalization for the internationalization you have two options 1 use the angular s i18n https angular io guide i18n system 2 use ngx translate http www ngx translate com library i won t go into details but the choice for this project and many other production like projects was to use ngx translate the main reasons are that for the same result it is simpler to use and develop with and angular i18n forces you to build the application per language and it reloads the application on language change further help to get more help on the angular cli use ng help or go check out the angular cli readme https github com angular angular cli blob master readme md vs code plugins if you are using vs code https code visualstudio com you may find the following plugins very helpful ts barrelr https marketplace visualstudio com items itemname mikerhyssmith ts barrelr automates the production of index ts barrel files jest runner https marketplace visualstudio com items itemname firsttris vscode jest runner simple way to run or debug a single or multiple jest tests from context menu as it is possible in intellij webstorm tslint https marketplace visualstudio com items itemname ms vscode vscode typescript tslint plugin adds tslint to vs code using the typescript tslint language service plugin typescript importer https marketplace visualstudio com items itemname pmneo tsimporter automatically searches for typescript definitions in workspace files and provides all known symbols as completion item to allow code completion license copyright by haythem ouederni all project sources are released under the apache license https github com haythem ouederni ng best practices blob master license license | angular angular-cli jest testing boilerplate best-practices ngxs facade-pattern tslint typescript commitizen prettier state-management store redux-like web-development mobile-development | front_end |
The-NLP-Pandect | the nlp pandect resources images pandect png p align center this pandect is ancient greek for encyclopedia was created to help you find almost anything related to natural language processing that is available online p p align center img src https emojipedia us s3 dualstack us west 1 amazonaws com thumbs 120 google 313 flag ukraine 1f1fa 1f1e6 png alt ukraine width 50 height 50 note quick legend on available resource types open source project usually a github repository with its number of stars resource you can read usually a blog post or a paper a collection of additional resources non open source tool framework or paid service a resource you can watch a resource you can listen to p align center b table of contents b p main section sub sections sample nlp resources https github com ivan bilan the nlp pandect paper summaries https github com ivan bilan the nlp pandect papers and paper summaries conference summaries https github com ivan bilan the nlp pandect conference summaries nlp datasets https github com ivan bilan the nlp pandect nlp datasets nlp podcasts https github com ivan bilan the nlp pandect 1 nlp only podcasts https github com ivan bilan the nlp pandect nlp only podcasts podcasts with many nlp episodes https github com ivan bilan the nlp pandect many nlp episodes nlp newsletters https github com ivan bilan the nlp pandect 2 nlp meetups https github com ivan bilan the nlp pandect 3 nlp youtube channels https github com ivan bilan the nlp pandect 4 nlp benchmarks https github com ivan bilan the nlp pandect 5 general nlu https github com ivan bilan the nlp pandect general nlu question answering https github com ivan bilan the nlp pandect question answering multilingual https github com ivan bilan the nlp pandect multilingual and non english benchmarks research resources https github com ivan bilan the nlp pandect 6 resource on transformer models https github com ivan bilan the nlp pandect transformer based architectures distillation and pruning https github com ivan bilan the nlp pandect distillation pruning and quantization automated summarization https github com ivan bilan the nlp pandect automated summarization industry resources https github com ivan bilan the nlp pandect 7 best practices for nlp systems https github com ivan bilan the nlp pandect best practices for nlp mlops for nlp https github com ivan bilan the nlp pandect mlops for nlp speech recognition https github com ivan bilan the nlp pandect 8 general resources https github com ivan bilan the nlp pandect general speech recognition text to speech https github com ivan bilan the nlp pandect text to speech speech to text https github com ivan bilan the nlp pandect speech to text datasets https github com ivan bilan the nlp pandect datasets topic modeling https github com ivan bilan the nlp pandect 9 blogs https github com ivan bilan the nlp pandect blogs 1 frameworks https github com ivan bilan the nlp pandect frameworks for topic modeling repositories and projects https github com ivan bilan the nlp pandect repositories 1 keyword extraction https github com ivan bilan the nlp pandect 10 text rank https github com ivan bilan the nlp pandect text rank rake https github com ivan bilan the nlp pandect rake rapid automatic keyword extraction other approaches https github com ivan bilan the nlp pandect other approaches responsible nlp https github com ivan bilan the nlp pandect 11 nlp and ml interpretability https github com ivan bilan the nlp pandect nlp and ml interpretability ethics bias and equality in nlp https github com ivan bilan the nlp pandect ethics bias and equality in nlp adversarial attacks for nlp https github com ivan bilan the nlp pandect adversarial attacks for nlp nlp frameworks https github com ivan bilan the nlp pandect 12 general purpose https github com ivan bilan the nlp pandect general purpose data augmentation https github com ivan bilan the nlp pandect data augmentation machine translation https github com ivan bilan the nlp pandect machine translation adversarial attacks https github com ivan bilan the nlp pandect adversarial nlp attacks behavioral testing dialog systems speech https github com ivan bilan the nlp pandect dialog systems and speech entity and string matching https github com ivan bilan the nlp pandect entity and string matching non english frameworks https github com ivan bilan the nlp pandect non english oriented text annotation https github com ivan bilan the nlp pandect text data labelling learning nlp https github com ivan bilan the nlp pandect 13 courses https github com ivan bilan the nlp pandect courses books https github com ivan bilan the nlp pandect books tutorials https github com ivan bilan the nlp pandect tutorials nlp communities https github com ivan bilan the nlp pandect 14 other nlp topics https github com ivan bilan the nlp pandect 15 tokenization https github com ivan bilan the nlp pandect tokenization data augmentation https github com ivan bilan the nlp pandect data augmentation and weak supervision named entity recognition https github com ivan bilan the nlp pandect named entity recognition ner error correction https github com ivan bilan the nlp pandect spell correction error correction automl autonlp https github com ivan bilan the nlp pandect automl autonlp text generation https github com ivan bilan the nlp pandect text generation the nlp resources resources images pandect resources png note section keywords paper summaries compendium awesome list compendiums and awesome lists on the topic of nlp the nlp index https index quantumstat com searchable index of nlp papers by quantum stat nlp cypher awesome nlp https github com keon awesome nlp by keon https github com keon github 13963 stars speech and natural language processing awesome list https github com edobashira speech language processing readme by elaboshira https github com edobashira github 2121 stars awesome deep learning for natural language processing nlp https github com brianspiering awesome dl4nlp github 1094 stars text mining and natural language processing resources https github com stepthom text mining resources by stepthom https github com stepthom github 505 stars made with ml list https madewithml com topics nlp by madewithml com https madewithml com brainsources for nlp enthusiasts https www notion so 634eba1a37d34e2baec1bb574a8a5482 by philip vollet https www linkedin com in philipvollet awesome ai ml dl nlp section https github com neomatrix369 awesome ai ml dl tree master natural language processing natural language processing nlp github 1142 stars resources on various machine learning topics https www backprop org by backprop nlp articles https devopedia org site map browse articles natural language processing by devopedia https devopedia org nlp conferences paper summaries and paper compendiums papers and paper summaries 100 must read nlp papers https github com mhagiwara 100 nlp papers 100 must read nlp papers github 3446 stars nlp paper summaries https github com dair ai nlp paper summaries by dair ai https github com dair ai github 1431 stars curated collection of papers for the nlp practitioner https github com mihail911 nlp library github 1059 stars papers on textual adversarial attack and defense https github com thunlp taadpapers github 1182 stars recent deep learning papers in nlu and rl https github com madrugado deep learning nlp rl papers by valentin malykh github 291 stars a survey of surveys nlp ml collection of nlp survey papers https github com niutrans abigsurvey github 1713 stars a paper list for style transfer in text https github com fuzhenxin style transfer in text github 1456 stars video recordings index for papers https papertalk org index conference summaries nlp top 10 conferences compendium https github com soulbliss nlp conference compendium by soulbliss https github com soulbliss github 439 stars iclr 2020 trends https gsarti com post iclr2020 transformers spacyirl 2019 conference in overview https www linkedin com pulse spacyirl 2019 conference overview ivan bilan paper digest https www paperdigest org category nlp conferences and papers in overview video recordings from conferences https crossminds ai explore nlp progress and nlp tasks nlp progress https github com sebastianruder nlp progress by sebastianruder https github com sebastianruder github 21123 stars nlp tasks https github com kyubyong nlp tasks by kyubyong https github com kyubyong github 2984 stars nlp datasets nlp datasets https github com niderhoff nlp datasets by niderhoff https github com niderhoff github 5225 stars datasets https github com huggingface datasets by huggingface github 14838 stars big bad nlp database https datasets quantumstat com uwa unambiguous word annotations http danlou github io uwa word sense disambiguation dataset mldoc https github com facebookresearch mldoc corpus for multilingual document classification in eight language github 145 stars word and sentence embeddings awesome embedding models https github com hironsan awesome embedding models by hironsan https github com hironsan github 1544 stars awesome list of sentence embeddings https github com separius awesome sentence embedding by separius https github com separius github 2086 stars awesome bert https github com jiakui awesome bert by jiakui https github com jiakui github 1797 stars notebooks scripts and repositories the super duper nlp repo https notebooks quantumstat com website 2020 non english resources and compendiums nlp resources for bahasa indonesian https github com louisowen6 nlp bahasa resources github 329 stars indic nlp catalog https github com ai4bharat indicnlp catalog github 381 stars pre trained language models for vietnamese https github com vinairesearch phobert github 491 stars natural language toolkit for indic languages inltk https github com goru001 inltk github 773 stars indic nlp library https github com anoopkunchukuttan indic nlp library github 448 stars ai4bharat indicnlp portal https indicnlp ai4bharat org arbml https github com arbml arbml implementation of many arabic nlp and ml projects github 284 stars zemberek nlp https github com ahmetaa zemberek nlp nlp tools for turkish github 1021 stars tdd ai https tdd ai an open source platform for all turkish datasets language models and nlp tools klue https github com klue benchmark klue korean language understanding evaluation github 468 stars persian nlp benchmark https github com mofid ai persian nlp benchmark benchmark for evaluation and comparison of various nlp tasks in persian language github 69 stars nlp greek https github com yuliya hv nlp greek greek language sources github 5 stars awesome nlp resources for hungarian https github com oroszgy awesome hungarian nlp github 160 stars pre trained nlp models list of pre trained nlp models https github com balavenkatesh3322 nlp pretrained model github 163 stars general pretrained language models https mr nlp github io posts 2022 07 general tptlms list blog july 2022 pretrained language models developed by huawei noah s ark lab https github com huawei noah pretrained language model github 2547 stars spanish language models and resources https github com plantl gob es lm spanish github 202 stars monolingual pretrained language models https mr nlp github io posts 2022 07 monolingual tptlms list collection of available pre trained models blog july 2022 nlp history general modern deep learning techniques applied to natural language processing https github com omarsar nlp overview github 1269 stars a review of the neural history of natural language processing https aylien com blog a review of the recent history of natural language processing blog october 2018 2020 year in review natural language processing in 2020 the year in review https www linkedin com pulse natural language processing 2020 year review ivan bilan blog december 2020 ml and nlp research highlights of 2020 https ruder io research highlights 2020 blog january 2021 the nlp podcasts resources images pandect lyra png back to the table of contents https github com ivan bilan the nlp pandect table of contents nlp only podcasts nlp highlights https soundcloud com nlp highlights years 2017 now status active the nlp zone https de player fm series the nlp zone episodes https player captivate fm episode e2f87641 1421 4729 a2b5 d64951c845c6 years 2021 now status active many nlp episodes twiml ai https twimlai com years 2016 now status active practical ai https changelog com practicalai years 2018 now status active the data exchange https thedataexchange media years 2019 now status active gradient dissent https www wandb com podcast years 2020 now status active machine learning street talk https open spotify com show 02e6pzeiodpmbgt9thuzwr years 2020 now status active dataframed https www datacamp com community podcast latest trends and insights on how to scale the impact of data science in organizations years 2019 now status active some nlp episodes the super data science podcast https www superdatascience com podcast years 2016 now status active data hack radio https soundcloud com datahack radio years 2018 now status active ai game changers https podcasts apple com de podcast ai game changers id1512574291 years 2020 now status active the analytics show https anchor fm analyticsshow years 2019 now status active the nlp newsletter resources images pandect scroll png nlp news https ruder io nlp news by sebastian ruder https ruder io dair ai newsletter https dair ai newsletter by dair ai dair ai this week in nlp by robert dale https www language technology com twin papers with code https paperswithcode com the batch https www deeplearning ai thebatch by deeplearning ai https www deeplearning ai thebatch paper digest https www paperdigest org 2020 04 recent papers on question answering by paperdigest https www paperdigest org daily paper digest nlp cypher https medium com quantumstat by quantumstat https quantumstat com the nlp meetups resources images pandect meetups png nlp zurich https www linkedin com company nlp zurich youtube recordings https www youtube com channel ucllx 5j9unyassows0nvedq hacking machine learning https www meetup com hacking machine learning youtube recordings https www youtube com channel uct5rvrc 3x7fnawhorvn7q ny nlp new york https www meetup com ny nlp the nlp youtube resources images pandect youtube png yannic kilcher https www youtube com channel uczhmqk67msjgfcctn7xbfew huggingface https www youtube com channel uchlnu7kizhrgsbhhvfoy72w kaggle reading group https www youtube com watch v phtf7yjnr70 list plqfatig4myu8t5ycqvp7i07jtjol3rcl9 rasa paper reading https www youtube com channel ucj0v6493mlvqdivwokwbodq playlists stanford cs224n nlp with deep learning https www youtube com watch v 8rxd5 xhemo list ploromvodv4rohcuxmzknm7j3fvwbby42z nlpxing https www youtube com channel ucugc1jusvvboga qmth3qa videos ml explained a i socratic circles aisc https www youtube com channel ucfk3ps8ccpxogoleriiufyg deeplearning ai https www youtube com channel uccixc5mjshvytzr1mal5l9w featured machine learning street talk https www youtube com channel ucmltbahi5dmrt0npvdsoirq featured the nlp benchmarks resources images pandect benchmark png back to the table of contents https github com ivan bilan the nlp pandect table of contents general nlu glue https gluebenchmark com general language understanding evaluation glue benchmark superglue https super gluebenchmark com benchmark styled after glue with a new set of more difficult language understanding tasks decanlp https decanlp com the natural language decathlon decanlp for studying general nlp models dialoglue https github com alexa dialoglue dialoglue a natural language understanding benchmark for task oriented dialogue github 235 stars dynabench https dynabench org dynabench is a research platform for dynamic data collection and benchmarking big bench https github com google big bench collaborative benchmark for measuring and extrapolating the capabilities of language models github 1228 stars summarization wikiasp https github com neulab wikiasp wikiasp multi document aspect based summarization dataset wikilingua https github com esdurmus wikilingua a multilingual abstractive summarization dataset question answering squad https rajpurkar github io squad explorer stanford question answering dataset squad xquad https github com deepmind xquad xquad cross lingual question answering dataset for cross lingual question answering grailqa https dki lab github io grailqa strongly generalizable question answering grailqa csqa https amritasaha1812 github io csqa complex sequential question answering multilingual and non english benchmarks xtreme https arxiv org abs 2003 11080 massively multilingual multi task benchmark gluecos https github com microsoft gluecos a benchmark for code switched nlp indicglue https indicnlp ai4bharat org indic glue natural language understanding benchmark for indic languages lince https ritual uh edu lince linguistic code switching evaluation benchmark russian superglue https russiansuperglue com russian superglue benchmark bio law and other scientific domains blurb https microsoft github io blurb biomedical language understanding and reasoning benchmark blue https github com ncbi nlp blue benchmark biomedical language understanding evaluation benchmark lexglue https github com coastalcph lex glue a benchmark dataset for legal language understanding in english transformer efficiency long range arena https github com google research long range arena long range arena for benchmarking efficient transformers pre print https arxiv org abs 2011 04006 github 481 stars speech processing superb http superbbenchmark org speech processing universal performance benchmark other codexglue https www microsoft com en us research blog codexglue a benchmark dataset and open challenge for code intelligence a benchmark dataset for code intelligence crossner https github com zliucr crossner crossner evaluating cross domain named entity recognition multinli cims nyu edu sbowman multinli multi genre natural language inference corpus isarcasm a dataset of intended sarcasm https github com silviu oprea isarcasm isarcasm is a dataset of tweets each labelled as either sarcastic or non sarcastic the nlp research resources images pandect quill png back to the table of contents https github com ivan bilan the nlp pandect table of contents general a recipe for training neural networks https karpathy github io 2019 04 25 recipe by andrej karpathy keywords research training 2019 recent advances in nlp via large pre trained language models a survey https arxiv org abs 2111 01243 paper november 2021 embeddings repositories pre trained elmo representations for many languages https github com hit scir elmoformanylangs github 1413 stars sense2vec https github com explosion sense2vec contextually keyed word vectors github 1449 stars wikipedia2vec https github com wikipedia2vec wikipedia2vec github 831 stars starspace https github com facebookresearch starspace github 3809 stars fasttext https github com facebookresearch fasttext github 24067 stars blogs language models and contextualised word embeddings http www davidsbatista net blog 2018 12 06 word embeddings by david s batista blog 2018 an essential guide to pretrained word embeddings for nlp practitioners https www analyticsvidhya com blog 2020 03 pretrained word embeddings nlp utm source avlinkedin utm medium post utm campaign 22 may new article by analyticsvidhya blog 2020 polyglot word embeddings discover language clusters http blog shriphani com 2020 02 03 polyglot word embeddings discover language clusters blog 2020 the illustrated word2vec https jalammar github io illustrated word2vec by jay alammar blog 2019 cross lingual word and sentence embeddings vecmap https github com artetxem vecmap vecmap cross lingual word embedding mappings github 604 stars sentence transformers https github com ukplab sentence transformers multilingual sentence image embeddings with bert github 8944 stars byte pair encoding bpemb https github com bheinzerling bpemb pre trained subword embeddings in 275 languages based on byte pair encoding bpe github 1081 stars subword nmt https github com rsennrich subword nmt unsupervised word segmentation for neural machine translation and text generation github 1972 stars python bpe https github com soaxelbrooke python bpe byte pair encoding for python github 188 stars transformer based architectures general the transformer family https lilianweng github io lil log 2020 04 07 the transformer family html by lilian weng blog 2020 playing the lottery with rewards and multiple languages https arxiv org abs 1906 02768 about the effect of random initialization iclr 2020 paper attention attention https lilianweng github io lil log 2018 06 24 attention attention html by lilian weng blog 2018 the transformer explained https nostalgebraist tumblr com post 185326092369 the transformer explained blog 2019 attention is all you need attentional neural network models https www youtube com watch v rbcqotefxvg by ukasz kaiser talk 2017 understanding and applying self attention for nlp https www youtube com watch v oyygpg4d9h0 talk 2018 the nlp cookbook modern recipes for transformer based deep learning architectures https arxiv org abs 2104 10640 paper april 2021 pre trained models past present and future https arxiv org abs 2106 07139 paper june 2021 a survey of transformers https arxiv org abs 2106 04554 paper june 2021 transformer the annotated transformer https nlp seas harvard edu 2018 04 03 attention html by harvard nlp blog 2018 the illustrated transformer http jalammar github io illustrated transformer by jay alammar blog 2018 illustrated guide to transformers https towardsdatascience com illustrated guide to transformer cf6969ffa067 by hong jing blog 2020 sequential transformer with adaptive attention span https github com facebookresearch adaptive span by facebook blog https ai facebook com blog making transformer networks simpler and more efficient blog 2019 evolution of representations in the transformer https lena voita github io posts emnlp19 evolution html by lena voita blog 2019 reformer the efficient transformer https ai googleblog com 2020 01 reformer efficient transformer html blog 2020 longformer the long document transformer https medium com dair ai longformer what bert should have been 78f4cd595be9 by viktor karlsson blog 2020 transformers from scratch http www peterbloem nl blog transformers blog 2019 universal transformers https mostafadehghani com 2019 05 05 universal transformers by mostafa dehghani blog 2019 transformers in natural language processing a brief survey https eigenfoo xyz transformers in nlp by george ho blog may 2020 lite transformer https github com mit han lab lite transformer lite transformer with long short range attention github 550 stars transformers from scratch https e2eml school transformers html blog oct 2021 bert a visual guide to using bert for the first time https jalammar github io a visual guide to using bert for the first time by jay alammar blog 2019 the dark secrets of bert https text machine lab github io blog 2020 bert secrets by anna rogers blog 2020 understanding searches better than ever before https www blog google products search search language understanding bert blog 2019 demystifying bert a comprehensive guide to the groundbreaking nlp framework https www analyticsvidhya com blog 2019 09 demystifying bert groundbreaking nlp framework blog 2019 sembert https github com cooelf sembert semantics aware bert for language understanding github 278 stars bertweet https github com vinairesearch bertweet bertweet a pre trained language model for english tweets github 487 stars optimal subarchitecture extraction for bert https github com alexa bort github 461 stars characterbert reconciling elmo and bert https github com helboukkouri character bert github 163 stars when bert plays the lottery all tickets are winning https thegradient pub when bert plays the lottery all tickets are winning blog dec 2020 bert related papers https github com tomohideshibata bert related papers a list of bert related papers github 1933 stars other transformer variants t5 t5 understanding transformer based self supervised architectures https medium com rojagtap t5 text to text transfer transformer 643f89e8905e blog august 2020 t5 the text to text transfer transformer https ai googleblog com 2020 02 exploring transfer learning with t5 html blog 2020 multilingual t5 https github com google research multilingual t5 multilingual t5 mt5 is a massively multilingual pretrained text to text transformer model github 956 stars bigbird big bird transformers for longer sequences https arxiv org abs 2007 14062 original paper by google research paper july 2020 reformer linformer longformer performers reformer the efficient transformer https arxiv org abs 2001 04451 paper february 2020 video https www youtube com watch v xjrkipwvwgm october 2020 longformer the long document transformer https arxiv org abs 2004 05150 paper april 2020 video https www youtube com watch v 8knb5iqble april 2020 linformer self attention with linear complexity https arxiv org abs 2006 04768 paper june 2020 video https www youtube com watch v 2af9lhweo june 2020 rethinking attention with performers https arxiv org abs 2009 14794 paper september 2020 video https www youtube com watch v 0etulzroztq september 2020 performer pytorch https github com lucidrains performer pytorch an implementation of performer a linear attention based transformer in pytorch github 898 stars switch transformer switch transformers scaling to trillion parameter models https arxiv org abs 2101 03961 original paper by google research paper january 2021 gpt family general the illustrated gpt 2 http jalammar github io illustrated gpt2 by jay alammar blog 2019 the annotated gpt 2 https amaarora github io 2020 02 18 annotatedgpt2 html by aman arora openai s gpt 2 the model the hype and the controversy https towardsdatascience com openais gpt 2 the model the hype and the controversy 1109f4bfd5e8 by ryan lowe blog 2019 how to generate text https huggingface co blog how to generate by patrick von platen blog 2020 gpt 3 learning resources zero shot learning for text classification https amitness com 2020 05 zero shot text classification by amit chaudhary blog 2020 gpt 3 a brief summary https leogao dev 2020 05 29 gpt 3 a brief summary by leo gao blog 2020 gpt 3 a giant step for deep learning and nlp https anotherdatum com gpt 3 html by yoel zeldes blog june 2020 gpt 3 language model a technical overview https lambdalabs com blog demystifying gpt 3 by chuan li blog june 2020 is it possible for language models to achieve language understanding https medium com chrisgpotts is it possible for language models to achieve language understanding 81df45082ee2 by christopher potts applications awesome gpt 3 https github com elyase awesome gpt3 list of all resources related to gpt 3 github 3773 stars gpt 3 projects https airtable com shrndwzex01al2jhm tblymaigedlxe35jc a map of all gpt 3 start ups and commercial projects gpt 3 demo showcase https gpt3demo com gpt 3 demo showcase 180 apps examples resources openai api https beta openai com api demo to use gpt 3 for commercial applications open source efforts gpt neo https eleuther ai projects gpt neo in progress gpt 3 open source replication huggingface hub https huggingface co eleutherai gpt j https github com kingoflolz mesh transformer jax gpt j 6b a 6 billion parameter autoregressive text generation model trained on the pile effectively using gpt j with few shot learning https nlpcloud io effectively using gpt j gpt neo gpt 3 alternatives few shot learning html blog july 2021 other what is two stream self attention in xlnet https towardsdatascience com what is two stream self attention in xlnet ebfe013a0cf3 by xu liang blog 2019 visual paper summary albert a lite bert https amitness com 2020 02 albert visual summary by amit chaudhary blog 2020 turing nlg https www microsoft com en us research blog turing nlg a 17 billion parameter language model by microsoft by microsoft multi label text classification with xlnet https towardsdatascience com multi label text classification with xlnet b5f5755302df by josh xin jie lee blog 2019 electra https github com google research electra github 2095 stars performer https github com lucidrains performer pytorch implementation of performer a linear attention based transformer in pytorch github 898 stars distillation pruning and quantization reading material distilling knowledge from neural networks to build smaller and faster models https blog floydhub com knowledge distillation by floydhub blog 2019 compression of deep learning models for text a survey https arxiv org abs 2008 05221 paper april 2021 tools bert squeeze https github com julesbelveze bert squeeze code to reduce the size of transformer based models or decrease their latency at inference time github 65 stars xtremedistil https github com microsoft xtreme distil transformers xtremedistiltransformers for distilling massive multilingual neural networks github 122 stars automated summarization pegasus a state of the art model for abstractive text summarization https ai googleblog com 2020 06 pegasus state of art model for html by google ai blog june 2020 ctrlsum https github com salesforce ctrl sum ctrlsum towards generic controllable text summarization github 128 stars xl sum https github com csebuetnlp xl sum xl sum large scale multilingual abstractive summarization for 44 languages github 186 stars summertime https github com yale lily summertime an open source text summarization toolkit for non experts github 211 stars primer https github com allenai primer primer pyramid based masked sentence pre training for multi document summarization github 107 stars summarus https github com ilyagusev summarus models for automatic abstractive summarization github 145 stars knowledge graphs and nlp fusing knowledge into language model https drive google com file d 1zgijg9rpxf tigwu9nt9rbcryoib4lok view presentation oct 2021 the nlp industry resources images pandect industry png note section keywords best practices mlops back to the table of contents https github com ivan bilan the nlp pandect table of contents best practices for building nlp projects in search of best practices for nlp projects https www youtube com watch v 0s9iai4ld4i slides https www dropbox com s 4fymdzz4yh3mlyz nlp best practices bilan pdf dl 0 dec 2020 emnlp 2020 high performance natural language processing https slideslive com 38940826 by google research recording https slideslive com 38940826 nov 2020 practical natural language processing https www amazon com practical natural language processing pragmatic dp 1492054054 a comprehensive guide to building real world nlp systems book june 2020 how to structure and manage nlp projects https neptune ai blog how to structure and manage nlp projects templates blog may 2021 applied nlp thinking https explosion ai blog applied nlp thinking applied nlp thinking how to translate problems into solutions blog june 2021 introduction to nlp for industry use https www youtube com watch v vrur3xey31s datatalksclub presentation on introduction to nlp for industry use recording december 2021 measuring embedding drift https arize com blog embedding drift best practices for monitoring drift of nlp models blog december 2022 mlops for nlp mlops especially when applied to nlp is a set of best practices around automating various parts of the workflow when building and deploying nlp pipelines in general mlops for nlp includes having the following processes in place data versioning make sure your training annotation and other types of data are versioned and tracked experiment tracking make sure that all of your experiments are automatically tracked and saved where they can be easily replicated or retraced model registry make sure any neural models you train are versioned and tracked and it is easy to roll back to any of them automated testing and behavioral testing besides regular unit and integration tests you want to have behavioral tests that check for bias or potential adversarial attacks model deployment and serving automate model deployment ideally also with zero downtime deploys like blue green canary deploys etc data and model observability track data drift model accuracy drift etc additionally there are two more components that are not as prevalent for nlp and are mostly used for computer vision and other sub fields of ai feature store centralized storage of all features developed for ml models than can be easily reused by any other ml project metadata management storage for all information related to the usage of ml models mainly for reproducing behavior of deployed ml models artifact tracking etc mlops compilations awesome lists awesome mlops https github com visenger awesome mlops github 8929 stars best of ml python https github com ml tooling best of ml python github 12011 stars mlops toys https mlops toys a curated list of mlops projects reading material machine learning operations mlops overview definition and architecture https arxiv org abs 2205 02302 paper may 2022 requirements and reference architecture for mlops insights from industry https www techrxiv org articles preprint requirements and reference architecture for mlops insights from industry 21397413 paper oct 2022 mlops what it is why it matters and how to implement it https neptune ai blog mlops what it is why it matters and how to implement it from a data scientist perspective by neptune ai blog july 2021 best mlops tools you need to know as a data scientist https neptune ai blog best mlops tools by neptune ai blog july 2021 robust mlops https blog verta ai blog robust mlops with open source modeldb docker jenkins and prometheus robust mlops with open source modeldb docker jenkins and prometheus blog may 2021 state of mlops 2021 https valohai com state of mlops introduction by valohai blog august 2021 the mlops stack https valohai com blog the mlops stack by valohai blog october 2020 data version control for machine learning applications https megagon ai blog data version control for machine learning applications by megagon ai blog july 2021 the rapid evolution of the canonical stack for machine learning https medium com odsc the rapid evolution of the canonical stack for machine learning 21b37af9c3b5 blog july 2021 mlops comprehensive beginner s guide https medium com sciforce mlops comprehensive beginners guide c235c77f407f blog march 2021 what i ve learned about mlops from speaking with 100 ml practitioners https veselinastaneva medium com what ive learned about mlops from speaking with 100 ml practitioners 3025e33458ad blog may 2021 datarobot challenger models https www datarobot com blog introducing mlops champion challenger models mlops champion challenger models state of mlops blog https www stateofmlops com by dr ori cohen mlops ecosystem overview https arize com wp content uploads 2021 04 arize ai ecosystem white paper pdf blog 2021 learning material mlops cource https madewithml com mlops by made with ml github mlops https mlops githubapp com collection of resources on how to facilitate machine learning ops with github ml observability fundamentals course https arize com ml observability fundamentals learn how to monitor and root cause issues with production nlp models mlops communities the mlops community https mlops community blogs slack group newsletter and more all about mlops data versioning dvc https dvc org data version control dvc tracks ml models and data sets free and open source link to github https github com iterative dvc weights biases https wandb ai site tools for experiment tracking and dataset versioning paid service pachyderm https www pachyderm com version control for data with the tools to build scalable end to end ml ai pipelines paid service with free tier experiment tracking mlflow https mlflow org open source platform for the machine learning lifecycle free and open source link to github https github com mlflow mlflow weights biases https wandb ai site tools for experiment tracking and dataset versioning paid service neptune ai https neptune ai experiment tracking and model registry built for research and production teams paid service comet ml https www comet ml site enables data scientists and teams to track compare explain and optimize experiments and models paid service sigopt https sigopt com automate training tuning visualize compare runs paid service optuna https github com optuna optuna hyperparameter optimization framework github 7255 stars clear ml https clear ml experiment orchestrate deploy and build data stores all in one place free and open source link to github https github com allegroai clearml metaflow https github com netflix metaflow human friendly python r library that helps scientists and engineers build and manage real life data science projects github 6187 stars model registry dvc https dvc org data version control dvc tracks ml models and data sets free and open source link to github https github com iterative dvc mlflow https mlflow org open source platform for the machine learning lifecycle free and open source link to github https github com mlflow mlflow modeldb https github com vertaai modeldb open source system for machine learning model versioning metadata and experiment management github 1530 stars neptune ai https neptune ai experiment tracking and model registry built for research and production teams paid service valohai https valohai com end to end ml pipelines paid service pachyderm https www pachyderm com version control for data with the tools to build scalable end to end ml ai pipelines paid service with free tier polyaxon https polyaxon com reproduce automate and scale your data science workflows with production grade mlops tools paid service comet ml https www comet ml site enables data scientists and teams to track compare explain and optimize experiments and models paid service automated testing and behavioral testing checklist https github com marcotcr checklist beyond accuracy behavioral testing of nlp models github 1806 stars textattack https github com qdata textattack framework for adversarial attacks data augmentation and model training in nlp github 2161 stars wildnlp https github com mi2datalab wildnlp corrupt an input text to test nlp models robustness github 74 stars great expectations https github com great expectations great expectations write tests for your data github 7703 stars deepchecks https github com deepchecks deepchecks python package for comprehensively validating your machine learning models and data github 2254 stars model deployability and serving mlflow https mlflow org open source platform for the machine learning lifecycle free and open source link to github https github com mlflow mlflow amazon sagemaker https aws amazon com de sagemaker paid service valohai https valohai com end to end ml pipelines paid service nlp cloud https nlpcloud io production ready nlp api paid service saturn cloud https saturncloud io paid service seldon https www seldon io tech machine learning deployment for enterprise paid service comet ml https www comet ml site enables data scientists and teams to track compare explain and optimize experiments and models paid service polyaxon https polyaxon com reproduce automate and scale your data science workflows with production grade mlops tools paid service torchserve https github com pytorch serve flexible and easy to use tool for serving pytorch models github 3008 stars kubeflow https www kubeflow org the machine learning toolkit for kubernetes github 10600 stars kfserving https github com kubeflow kfserving serverless inferencing on kubernetes github 1841 stars tfx https www tensorflow org tfx tensorflow extended end to end platform for deploying production ml pipelines paid service pachyderm https www pachyderm com version control for data with the tools to build scalable end to end ml ai pipelines paid service with free tier cortex https www cortex dev containers as a service on aws paid service azure machine learning https azure microsoft com en us services machine learning features end to end machine learning lifecycle paid service end2end serverless transformers on aws lambda https github com bhavsarpratik serverless transformers on aws lambda github 110 stars nlp service https github com karndeb nlp service sample demo of nlp as a service platform built using fastapi and hugging face github 13 stars dagster https dagster io data orchestrator for machine learning free and open source verta https www verta ai ai and machine learning deployment and operations paid service metaflow https github com netflix metaflow human friendly python r library that helps scientists and engineers build and manage real life data science projects github 6187 stars flyte https github com flyteorg flyte workflow automation platform for complex mission critical data and ml processes at scale github 2887 stars mlrun https github com mlrun mlrun machine learning automation and tracking github 856 stars datarobot mlops https www datarobot com platform mlops datarobot mlops provides a center of excellence for your production ai model debugging imodels https github com csinva imodels package for concise transparent and accurate predictive modeling github 971 stars cockpit https github com f dangel cockpit a practical debugging tool for training deep neural networks github 416 stars model accuracy prediction weightwatcher https github com calculatedcontent weightwatcher weightwatcher tool for predicting the accuracy of deep neural networks github 1028 stars data and model observability general arize ai https arize com embedding drift monitoring for nlp models arize phoenix https phoenix arize com ml observability for llms vision language and tabular models whylogs https github com whylabs whylogs open source standard for data and ml logging github 1907 stars rubrix https github com recognai rubrix open source tool for exploring and iterating on data for artificial intelligence projects github 1450 stars mlrun https github com mlrun mlrun machine learning automation and tracking github 856 stars datarobot mlops https www datarobot com platform mlops datarobot mlops provides a center of excellence for your production ai cortex https www cortex dev containers as a service on aws paid service model centric algorithmia https algorithmia com minimize risk with advanced reporting and enterprise grade security and governance across all data models and infrastructure paid service dataiku https www dataiku com dataiku is for teams who want to deliver advanced analytics using the latest techniques at big data scale paid service evidently ai https evidentlyai com tools to analyze and monitor machine learning models free and open source link to github https github com evidentlyai evidently fiddler https www fiddler ai ml model performance management tool paid service hydrosphere https hydrosphere io open source platform for managing ml models paid service verta https www verta ai ai and machine learning deployment and operations paid service domino model ops https www dominodatalab com product model ops deploy and manage models to drive business impact paid service iguazio https www iguazio com deployment and management of your ai applications with mlops and end to end automation of machine learning pipelines paid service data centric datafold https www datafold com data quality through diffs profiling and anomaly detection paid service acceldata https www acceldata io improve reliability accelerate scale and reduce costs across all data pipelines paid service bigeye https www bigeye com monitoring and alerting to your datasets in minutes paid service datakin https datakin com product end to end real time data lineage solution paid service monte carlo https www montecarlodata com data integrity drifts schema lineage paid service soda https www soda io data monitoring testing and validation paid service whatify https whatify ai data quality and action recommendation on it paid service feature stores tecton https www tecton ai enterprise feature store for machine learning paid service feast https github com feast dev feast open source feature store for machine learning website https feast dev github 3792 stars hopsworks feature store https www hopsworks ai feature store data management system for managing machine learning features paid service metadata management ml metadata https github com google ml metadata a library for recording and retrieving metadata associated with ml developer and data scientist workflows github 500 stars neptune ai https neptune ai experiment tracking and model registry built for research and production teams paid service mlops frameworks metaflow https github com netflix metaflow human friendly python r library that helps scientists and engineers build and manage real life data science projects github 6187 stars kedro https github com quantumblacklabs kedro python framework for creating reproducible maintainable and modular data science code github 7865 stars seldon core https github com seldonio seldon core mlops framework to package deploy monitor and manage thousands of production machine learning models github 3503 stars zenml https github com maiot io zenml mlops framework to create reproducible ml pipelines for production machine learning github 2549 stars google vertex ai https cloud google com vertex ai build deploy and scale ml models faster with pre trained and custom tooling within a unified ai platform paid service diffgram https github com diffgram diffgram complete training data platform for machine learning delivered as a single application github 1583 stars continual ai https continual ai build deploy and operationalize ml models easier and faster with a declarative interface on cloud data warehouses like snowflake bigquery redshift and databricks paid service transformer based architectures back to the table of contents https github com ivan bilan the nlp pandect table of contents general why bert fails in commercial environments https www intel com content www us en artificial intelligence posts bert commercial environments html by intel ai blog 2020 fine tuning bert for text classification with farm https towardsdatascience com fine tuning bert for text classification with farm 2880665065e2 by sebastian guggisberg blog 2020 pretrain transformers models in pytorch using hugging face transformers https github com gmihaila ml things blob master notebooks pytorch pretrain transformers pytorch ipynb github 186 stars practical nlp for the real world https www infoq com presentations practical nlp presentation 2019 from paper to product how we implemented bert https www youtube com watch v vnmkdpbqjjk by christoph henkelmann talk 2020 multi gpu transformers parallelformers an efficient model parallelization toolkit for deployment https github com tunib ai parallelformers github 548 stars training transformers effectively training bert with compute time academic budget https github com intellabs academic budget bert github 256 stars embeddings as a service embedding as service https github com amansrivastava17 embedding as service github 176 stars bert as service https github com hanxiao bert as service github 11035 stars nlp recipes industrial applications nlp recipes https github com microsoft nlp recipes by microsoft https github com microsoft github 6048 stars nlp with python https github com susanli2016 nlp with python by susanli2016 https github com susanli2016 github 2454 stars basic utilities for pytorch nlp https github com petrochukm pytorch nlp by petrochukm https github com petrochukm github 2127 stars nlp applications in bio finance legal and other industries blackstone https github com iclrandd blackstone a spacy pipeline and model for nlp on unstructured legal text github 573 stars sci spacy https github com allenai scispacy spacy pipeline and models for scientific biomedical documents github 1279 stars finbert pre trained on sec filings for financial nlp tasks https github com psnonis finbert github 165 stars lexnlp https github com lexpredict lexpredict lexnlp information retrieval and extraction for real unstructured legal text github 555 stars nerdl and nercrf https github com johnsnowlabs spark nlp workshop blob master tutorials blogposts data prep ipynb tutorial on named entity recognition for healthcare with sparknlp legal text analytics https github com liquid legal institute legal text analytics a list of selected resources dedicated to legal text analytics github 410 stars bioie https github com caufieldjh awesome bioie a curated list of resources relevant to doing biomedical information extraction github 222 stars the nlp speech resources images pandect speech png note section keywords speech recognition back to the table of contents https github com ivan bilan the nlp pandect table of contents general speech recognition wav2letter https github com facebookresearch wav2letter automatic speech recognition toolkit github 6149 stars deepspeech https github com mozilla deepspeech baidu s deepspeech architecture github 20639 stars acoustic word embeddings https medium com maobedkova acoustic word embeddings fc3f1a8f0519 by maria obedkova blog 2020 kaldi https github com kaldi asr kaldi kaldi is a toolkit for speech recognition github 12177 stars awesome kaldi https github com yoavramon awesome kaldi resources for using kaldi github 510 stars espnet https github com espnet espnet end to end speech processing toolkit github 5791 stars hubert https ai facebook com blog hubert self supervised representation learning for speech recognition generation and compression self supervised representation learning for speech recognition generation and compression blog june 2021 text to speech fastspeech https github com xcmyz fastspeech the implementation of fastspeech based on pytorch github 746 stars tts https github com coqui ai tts a deep learning toolkit for text to speech github 7214 stars speech to text whisper https github com openai whisper robust speech recognition via large scale weak supervision by openai github 17097 stars datasets voxpopuli https github com facebookresearch voxpopuli large scale multilingual speech corpus for representation learning github 392 stars the nlp topics resources images pandect topics png note section keywords topic modeling back to the table of contents https github com ivan bilan the nlp pandect table of contents blogs topic modelling with pyspark and spark nlp https medium com trustyou engineering topic modelling with pyspark and spark nlp a99d063f1a6e by maria obedkova spark blog 2020 a unique approach to short text clustering algorithmic theory https towardsdatascience com a unique approach to short text clustering part 1 algorithmic theory 4d4fad0882e1 by brittany bowers blog 2020 frameworks for topic modeling gensim https github com rare technologies gensim framework for topic modeling github 13760 stars spark nlp https github com johnsnowlabs spark nlp github 3018 stars repositories top2vec https github com ddangelov top2vec github 2325 stars anchored correlation explanation topic modeling https github com gregversteeg corex github 289 stars topic modeling in embedding spaces https github com adjidieng etm github 480 stars paper https arxiv org abs 1907 04907 topicnet https github com machine intelligence laboratory topicnet a high level interface for bigartm library github 128 stars bertopic https github com maartengr bertopic leveraging bert and a class based tf idf to create easily interpretable topics github 3426 stars octis https github com mind lab octis a python package to optimize and evaluate topic models github 457 stars contextualized topic models https github com milanlproc contextualized topic models github 968 stars gsdmm https github com rwalk gsdmm gsdmm short text clustering github 305 stars keyword extraction resources images pandect papyrus2 png note section keywords keyword extraction back to the table of contents https github com ivan bilan the nlp pandect table of contents text rank pytextrank https github com derwenai pytextrank pytextrank is a python implementation of textrank as a spacy pipeline extension github 1933 stars textrank https github com summanlp textrank textrank implementation for python 3 github 1158 stars rake rapid automatic keyword extraction rake nltk https github com csurfer rake nltk rapid automatic keyword extraction algorithm using nltk github 956 stars yake https github com liaad yake single document unsupervised keyword extraction github 1238 stars rake tutorial https github com zelandiya rake tutorial a python implementation of the rapid automatic keyword extraction github 369 stars rake nltk https github com csurfer rake nltk rapid automatic keyword extraction algorithm using nltk github 956 stars other approaches flashtext https github com vi3k6i5 flashtext extract keywords from sentence or replace keywords in sentences github 5318 stars bert keyword extractor https github com ibatra bert keyword extractor deep keyphrase extraction using bert github 225 stars keybert https github com maartengr keybert minimal keyword extraction with bert github 1998 stars keyphrasevectorizers https github com timschopf keyphrasevectorizers vectorizers that extract keyphrases with part of speech patterns github 117 stars further reading adding a custom tokenizer to spacy and extracting keywords from chinese texts https howard haowen github io blog ai keyword extraction spacy textacy ckip transformers jieba textrank rake 2021 02 16 adding a custom tokenizer to spacy and extracting keywords html by haowen jiang blog feb 2021 how to extract relevant keywords with keybert https towardsdatascience com how to extract relevant keywords with keybert 6e7b3cf889ae blog june 2021 responsible nlp resources images pandect pegasus png note section keywords ethics responsible nlp back to the table of contents https github com ivan bilan the nlp pandect table of contents nlp and ml interpretability nlp centric explainability for natural language processing kdd 2021 tutorial https www youtube com watch v pvkosygclpk t 2s slides https www slideshare net yunyaoli explainability for natural language processing 249992241 presentation august 2021 ecco https github com jalammar ecco tools to visuals and explore nlp language models github 1548 stars nlp profiler https github com neomatrix369 nlp profiler a simple nlp library allows profiling datasets with text columns github 223 stars transformers interpret https github com cdpierse transformers interpret model explainability that works seamlessly with transformers github 905 stars awesome explainable ai https github com wangyongjie ntu awesome explainable ai collection of research materials on explainable ai ml github 780 stars lama https github com facebookresearch lama lama is a probe for analyzing the factual and commonsense knowledge contained in pretrained language models github 956 stars general language interpretability tool lit https github com pair code lit github 3020 stars whatlies https github com rasahq whatlies toolkit to help visualise what lies in word embeddings github 435 stars interpret text https github com interpretml interpret text interpretability techniques and visualization dashboards for nlp models github 340 stars interpretml https github com interpretml interpret fit interpretable models explain blackbox machine learning github 5155 stars thermostat https github com dfki nlp thermostat collection of nlp model explanations and accompanying analysis tools github 126 stars dodrio https github com poloclub dodrio exploring attention weights in transformer based models with linguistic knowledge github 245 stars imodels https github com csinva imodels package for concise transparent and accurate predictive modeling github 971 stars ethics bias and equality in nlp bias in natural language processing emnlp 2020 https gaurav maheshwari medium com bias in natural language processing emnlp 2020 8f1cb2806fcc cc1a blog nov 2020 machine learning as a software engineering enterprise https nips cc virtual 2020 public invited 16166 html neurips 2020 keynote presentation dec 2020 computational ethics for nlp http demo clab cs cmu edu ethical nlp course resources from the carnegie mellon university lecture notes spring 2020 ethics in nlp https aclweb org aclwiki ethics in nlp resources from acls ethics in nlp track the institute for ethical ai machine learning https ethical institute understanding the capabilities limitations and societal impact of large language models https arxiv org abs 2102 02503 paper feb 2021 fairness in ai https github com dreji18 fairness in ai this package is used to detect and mitigate biases in nlp tasks github 24 stars nlg bias https github com ewsheng nlg bias dataset classifier tools to study social perception biases in natural language generation github 46 stars bias in nlp https github com cisnlp bias in nlp list of papers related to bias in nlp github 9 stars adversarial attacks for nlp privacy considerations in large language models https ai googleblog com 2020 12 privacy considerations in large html m 1 blog dec 2020 deepwordbug https github com qdata deepwordbug generation of adversarial text sequences to evade deep learning classifiers github 57 stars adversarial misspellings https github com danishpruthi adversarial misspellings combating adversarial misspellings with robust word recognition github 57 stars hate speech analysis hatexplain https github com hate alert hatexplain bert for detecting abusive language github 135 stars the nlp frameworks resources images pandect frameworks png note section keywords frameworks back to the table of contents https github com ivan bilan the nlp pandect table of contents general purpose spacy https github com explosion spacy by explosion ai github 24708 stars flair https github com flairnlp flair by zalando github 12278 stars allennlp https github com allenai allennlp by ai2 github 11314 stars stanza https github com stanfordnlp stanza former stanford nlp github 6413 stars spacy stanza https github com explosion spacy stanza github 660 stars nltk https github com nltk nltk github 11280 stars gensim https github com rare technologies gensim framework for topic modeling github 13760 stars pororo https github com kakaobrain pororo platform of neural models for natural language processing github 1164 stars nlp architect https github com nervanasystems nlp architect a deep learning nlp nlu library by intel ai lab github 2883 stars farm https github com deepset ai farm github 1597 stars gobbli https github com rtiinternational gobbli by rti international github 268 stars headliner https github com as ideas headliner training and deployment of seq2seq models github 231 stars syfertext https github com openmined syfertext a privacy preserving nlp framework github 190 stars detext https github com linkedin detext text understanding framework for ranking and classification tasks github 1230 stars texthero https github com jbesomi texthero text preprocessing representation and visualization github 2635 stars textblob https github com sloria textblob textblob simplified text processing github 8373 stars adaptnlp https github com novetta adaptnlp a high level framework and library for nlp github 407 stars textacy https github com chartbeat labs textacy nlp before and after spacy github 1999 stars texar https github com asyml texar toolkit for machine learning natural language processing and text generation in tensorflow github 2323 stars jiant https github com nyu mll jiant jiant is an nlp toolkit github 1449 stars data augmentation wildnlp https github com mi2datalab wildnlp text manipulation library to test nlp models github 74 stars snorkel https github com snorkel team snorkel framework to generate training data github 5338 stars nlpaug https github com makcedward nlpaug data augmentation for nlp github 3665 stars sentaugment https github com facebookresearch sentaugment data augmentation by retrieving similar sentences from larger datasets github 361 stars faker https github com joke2k faker python package that generates fake data for you github 15129 stars textflint https github com textflint textflint unified multilingual robustness evaluation toolkit for nlp github 585 stars parrot https github com prithivirajdamodaran parrot paraphraser practical and feature rich paraphrasing framework github 636 stars augly https github com facebookresearch augly data augmentations library for audio image text and video github 4616 stars textaugment https github com dsfsi textaugment python 3 library for augmenting text for natural language processing applications github 290 stars adversarial nlp attacks behavioral testing textattack https github com qdata textattack framework for adversarial attacks data augmentation and model training in nlp github 2161 stars cleverhans https github com tensorflow cleverhans adversarial example library for constructing nlp attacks and building defenses github 5660 stars checklist https github com marcotcr checklist beyond accuracy behavioral testing of nlp models github 1806 stars transformer oriented transformers https github com huggingface transformers by huggingface github 75428 stars adapter hub https github com adapter hub adapter transformers and its documentation https docs adapterhub ml index html adapter modules for transformers github 1110 stars haystack https github com deepset ai haystack transformers at scale for question answering neural search github 6147 stars dialog systems and speech deeppavlov https github com deepmipt deeppavlov by mipt github 5933 stars parlai https github com facebookresearch parlai by fair github 9640 stars rasa https github com rasahq rasa framework for conversational agents github 15150 stars wav2letter https github com facebookresearch wav2letter automatic speech recognition toolkit github 6149 stars chatterbot https github com gunthercox chatterbot conversational dialog engine for creating chat bots github 12696 stars speechbrain https github com speechbrain speechbrain open source and all in one speech toolkit based on pytorch github 4935 stars word sentence embeddings oriented muse https github com facebookresearch muse a library for multilingual unsupervised or supervised word embeddings github 3021 stars vecmap https github com artetxem vecmap a framework to learn cross lingual word embedding mappings github 604 stars sentence transformers https github com ukplab sentence transformers multilingual sentence image embeddings with bert github 8944 stars social media oriented ekphrasis https github com cbaziotis ekphrasis text processing tool geared towards text from social networks github 592 stars phonetics deepphonemizer https github com as ideas deepphonemizer grapheme to phoneme conversion with deep learning github 197 stars morphology lemminflect https github com bjascob lemminflect python module for english lemmatization and inflection github 186 stars inflect https github com jaraco inflect generate plurals ordinals indefinite articles github 757 stars simplemma https github com jaraco inflect simple multilingual lemmatizer for python github 757 stars multi lingual tools polyglot https github com abosamoor polyglot multi lingual nlp framework github 2086 stars trankit https github com nlp uoregon trankit light weight transformer based python toolkit for multilingual nlp github 649 stars distributed nlp multi gpu nlp spark nlp https github com johnsnowlabs spark nlp github 3018 stars parallelformers an efficient model parallelization toolkit for deployment https github com tunib ai parallelformers github 548 stars machine translation comet https github com unbabel comet a neural framework for mt evaluation github 191 stars marian nmt https github com marian nmt marian fast neural machine translation in c github 974 stars argos translate https github com argosopentech argos translate open source neural machine translation in python github 1535 stars opus mt https github com helsinki nlp opus mt open neural machine translation models and web services github 257 stars dl translate https github com xhlulu dl translate a deep learning based translation library built on huggingface transformers github 241 stars entity and string matching polyfuzz https github com maartengr polyfuzz fuzzy string matching grouping and evaluation github 589 stars pyahocorasick https github com wojciechmula pyahocorasick python module implementing aho corasick algorithm for string matching github 757 stars fuzzywuzzy https github com seatgeek fuzzywuzzy fuzzy string matching in python github 8776 stars jellyfish https github com jamesturk jellyfish approximate and phonetic matching of strings github 1759 stars textdistance https github com life4 textdistance compute distance between sequences github 3000 stars deepmatcher https github com anhaidgroup deepmatcher compute distance between sequences github 457 stars re2 https github com alibaba edu simple effective text matching simple and effective text matching with richer alignment features github 336 stars machamp https github com megagonlabs machamp machamp a generalized entity matching benchmark github 9 stars discourse analysis convokit https github com cornellnlp cornell conversational analysis toolkit cornell conversational analysis toolkit github 399 stars pii scrubbing scrubadub https github com leapbeyond scrubadub clean personally identifiable information from dirty dirty text github 309 stars hastag segmentation hashformers https github com ruanchaves hashformers automatically inserting the missing spaces between the words in a hashtag github 41 stars books analysis literary analysis booknlp https github com booknlp booknlp a natural language processing pipeline that scales to books and other long documents in english github 647 stars bookworm https github com harrisonpim bookworm ingests novels builds an implicit character network and a deeply analysable graph github 73 stars non english oriented japanese fugashi https github com polm fugashi cython mecab wrapper for fast pythonic japanese tokenization and morphological analysis github 268 stars sudachipy https github com worksapplications sudachipy sudachipy is a python version of sudachi a japanese morphological analyzer github 330 stars konoha https github com himkt konoha easy to use japanese text processing tool which makes it possible to switch tokenizers with small changes of code github 182 stars jprocessing https github com kevincobain2000 jprocessing japanese natural langauge processing libraries github 142 stars ginza https github com megagonlabs ginza japanese nlp library using spacy as framework based on universal dependencies github 620 stars kuromoji https github com atilika kuromoji self contained and very easy to use japanese morphological analyzer designed for search github 847 stars nagisa https github com taishi i nagisa japanese tokenizer based on recurrent neural networks github 321 stars kytea https github com neubig kytea kyoto text analysis toolkit for word segmentation and pronunciation estimation github 190 stars jigg https github com mynlp jigg pipeline framework for easy natural language processing github 72 stars juman https github com ku nlp jumanpp juman a morphological analyzer toolkit github 321 stars rakutenma https github com rakuten nlp rakutenma morphological analyzer word segmentor pos tagger for chinese and japanese written purely in javascript github 447 stars toiro https github com taishi i toiro a comparison tool of japanese tokenizers github 105 stars thai attacut https github com pythainlp attacut fast and reasonably accurate word tokenizer for thai github 68 stars thailmcut https github com meanna thailmcut word tokenizer for thai language github 15 stars chinese spacy pkuseg https github com explosion spacy pkuseg the pkuseg toolkit for multi domain chinese word segmentation github 20 stars other textblob de https github com markuskiller textblob de textblob simplified text processing for german github 95 stars kashgari https github com brikerman kashgari transfer learning with focus on chinese github 2333 stars underthesea https github com undertheseanlp underthesea vietnamese nlp toolkit github 1057 stars ptt5 https github com unicamp dl ptt5 pretraining and validating the t5 model on brazilian portuguese data github 62 stars text data labelling small text https github com webis de small text active learning for text classifcation in python github 369 stars doccano https github com doccano doccano open source annotation tool for machine learning practitioners github 7005 stars prodigy https prodi gy annotation tool powered by active learning paid service the nlp learning resources images pandect learning png note section keywords learn nlp back to the table of contents https github com ivan bilan the nlp pandect table of contents general learn nlp the practical way https towardsdatascience com learn nlp the practical way b854ce1035c4 blog nov 2019 learn nlp the stanford way https towardsdatascience com learn nlp the stanford way lesson 1 3f1844265760 part 2 https towardsdatascience com learn nlp the stanford way lesson 2 7447f2c12b36 blog nov 2020 choosing the right course for a practical nlp engineer https airev us ultimate guide to natural language processing courses 12 best natural language processing courses tutorials to learn online https blog coursesity com best natural language processing courses treasure of transformers https github com ashishpatel26 treasure of transformers natural language processing papers videos blogs official repos along with colab notebooks github 563 stars rasa algorithm whiteboard https www youtube com playlist list pl75e0qa87dlg za8eli6t0 pbxafk cxb youtube series by rasa explaining various data science and nlp algorithms explosionai videos https www youtube com c explosionai videos youtube series by explosionai teaching you how to use spacy and apply it for nlp courses cs25 transformers united stanford fall 2021 https web stanford edu class cs25 course fall 2021 nlp course for you https lena voita github io nlp course html great and interactive course on nlp openclass nlp https openclass ai catalog nlp natural language processing nlp assignments advanced nlp with spacy https course spacy io en how to use spacy to build advanced natural language understanding systems transformer models for nlp https huggingface co course chapter1 by huggingface stanford nlp seminar https nlp stanford edu seminar slides from the stanford nlp course books natural language processing with transformers https www buecher de shop maschinelles lernen natural language processing with transformers tunstall lewis von werra leandro wolf thomas products products detail prod id 64140211 book february 2022 applied natural language processing in the enterprise https www oreilly com library view applied natural language 9781492062561 book may 2021 practical natural language processing https www oreilly com library view practical natural language 9781492054047 book june 2020 dive into deep learning https d2l ai index html an interactive deep learning book with code math and discussions natural language processing and computational linguistics https www amazon de natural language processing computational linguistics dp 1848218486 speech morphology and syntax cognitive science top nlp books to read 2020 https towardsdatascience com top nlp books to read 2020 12012ef41dc1 blog post by raymong cheng blog sep 2020 tutorials nlp tutorial https github com lyeoni nlp tutorial a list of nlp natural language processing tutorials built on pytorch github 1324 stars nlp tutorial https github com graykode nlp tutorial natural language processing tutorial for deep learning researchers github 11796 stars hands on nltk tutorial https github com hb20007 hands on nltk tutorial github 506 stars modern practical natural language processing https github com jmugan modern practical nlp github 260 stars transformers tutorials https github com nielsrogge transformers tutorials demos with the transformers library by huggingface github 3408 stars calmcode tutorials https calmcode io science set of python data science tutorials the nlp communities resources images pandect communities png r languagetechnology https www reddit com r languagetechnology nlp reddit forum other nlp topics resources images pandect papyrus other png back to the table of contents https github com ivan bilan the nlp pandect table of contents tokenization tokenizers https github com huggingface tokenizers fast state of the art tokenizers optimized for research and production github 6064 stars sentencepiece https github com google sentencepiece unsupervised text tokenizer for neural network based text generation github 6316 stars somajo https github com tsproisl somajo a tokenizer and sentence splitter for german and english web and social media texts github 108 stars data augmentation and weak supervision libraries and frameworks wildnlp https github com mi2datalab wildnlp text manipulation library to test nlp models github 74 stars nlpaug https github com makcedward nlpaug data augmentation for nlp github 3665 stars sentaugment https github com facebookresearch sentaugment data augmentation by retrieving similar sentences from larger datasets github 361 stars textattack https github com qdata textattack framework for adversarial attacks data augmentation and model training in nlp github 2161 stars skweak https github com norskregnesentral skweak software toolkit for weak supervision applied to nlp tasks github 843 stars nl augmenter https github com gem benchmark nl augmenter collaborative repository of natural language transformations github 679 stars eda https github com jasonwei20 eda nlp easy data augmentation techniques for boosting performance on text classification tasks github 1356 stars snorkel https github com snorkel team snorkel framework to generate training data github 5338 stars reading material and tutorials a survey of data augmentation approaches for nlp https arxiv org abs 2105 03075 paper may 2021 github link https github com styfeng dataaug4nlp a visual survey of data augmentation in nlp https amitness com 2020 05 data augmentation for nlp blog 2020 weak supervision a new programming paradigm for machine learning http ai stanford edu blog weak supervision blog march 2019 named entity recognition ner datasets for entity recognition https github com juand r entity recognition datasets github 1255 stars datasets to train supervised classifiers for named entity recognition https github com davidsbatista ner datasets github 297 stars bootleg https github com hazyresearch bootleg self supervision for named entity disambiguation at the tail github 189 stars few nerd https github com thunlp few nerd large scale fine grained manually annotated named entity recognition dataset github 318 stars relation extraction tacred relation https github com yuhaozhang tacred relation tacred position aware attention model for relation extraction github 336 stars tacrev https github com dfki nlp tacrev tacred revisited a thorough evaluation of the tacred relation extraction task github 55 stars tac self attention https github com ivan bilan tac self attention relation extraction with position aware self attention github 64 stars re tacred https github com gstoica27 re tacred re tacred addressing shortcomings of the tacred dataset github 39 stars coreference resolution neuralcoref 4 0 coreference resolution in spacy with neural networks https github com huggingface neuralcoref by huggingface github 2627 stars coref https github com mandarjoshi90 coref bert and spanbert for coreference resolution github 399 stars sentiment analysis reading list for awesome sentiment analysis papers https github com declare lab awesome sentiment analysis by declare lab https github com declare lab github 475 stars awesome sentiment analysis https github com xiamx awesome sentiment analysis by xiamx https github com xiamx github 884 stars domain adaptation neural adaptation in natural language processing curated list https github com bplank awesome neural adaptation in nlp github 246 stars low resource nlp cmu lti low resource nlp bootcamp 2020 https github com neubig lowresource nlp bootcamp 2020 cmu language technologies institute low resource nlp bootcamp 2020 github 555 stars spell correction error correction gramformer https github com prithivirajdamodaran gramformer ramework for detecting highlighting and correcting grammatical errors github 1244 stars neuspell https github com neuspell neuspell a neural spelling correction toolkit github 515 stars symspellpy https github com mammothb symspellpy python port of symspell github 641 stars speller100 https www microsoft com en us research blog speller100 zero shot spelling correction at scale for 100 plus languages by microsoft blog feb 2021 jamspell https github com bakwc jamspell spell checking library accurate fast multi language github 527 stars pycorrector https github com shibing624 pycorrector spell correction for chinese github 3714 stars contractions https github com kootenpv contractions fixes contractions such as you re to you are github 262 stars style transfer for nlp styleformer https github com prithivirajdamodaran styleformer neural language style transfer framework github 427 stars styleptb https github com lvyiwei1 styleptb a compositional benchmark for fine grained controllable text style transfer github 51 stars automata theory for nlp pyahocorasick https github com wojciechmula pyahocorasick python module implementing aho corasick algorithm for string matching github 757 stars obscene words detection ldnoobw https github com ldnoobw list of dirty naughty obscene and otherwise bad words list of dirty naughty obscene and otherwise bad words github 1988 stars reddit analysis subreddit analyzer https github com phantominsights subreddit analyzer comprehensive data and text mining workflow for submissions and comments from any given public subreddit github 483 stars skill detection skillner https github com anasaito skillner rule based nlp module to extract job skills from text github 71 stars reinforcement learning for nlp nlp gym https github com rajcscw nlp gym nlpgym a toolkit to develop rl agents to solve nlp tasks github 132 stars automl autonlp autonlp https github com huggingface autonlp faster and easier training and deployments of sota nlp models github 689 stars tpot https github com epistasislab tpot python automated machine learning tool github 8826 stars auto pytorch https github com automl auto pytorch automatic architecture search and hyperparameter optimization for pytorch github 1862 stars hungabunga https github com ypeleg hungabunga brute force all sklearn models with all parameters using fit predict github 674 stars automl natural language https cloud google com natural language automl docs google s paid automl nlp service optuna https github com optuna optuna hyperparameter optimization framework github 7255 stars flaml https github com microsoft flaml fast and lightweight automl library github 2154 stars gradsflow https github com gradsflow gradsflow open source automl pytorch model training library github 289 stars ocr optical character recognition a framework for designing document processing solutions https ljvmiranda921 github io notebook 2022 06 19 document processing framework blog june 2022 document ai table transformer https huggingface co docs transformers main model doc table transformer huggingface models https huggingface co models other table transformer text generation keytotext https github com gagan3012 keytotext a model which will take keywords as inputs and generate sentences as outputs github 353 stars controllable neural text generation https lilianweng github io lil log 2021 01 02 controllable neural text generation html blog jan 2021 bartscore https github com neulab bartscore evaluating generated text as text generation github 192 stars title headlines generation titlestylist https github com jind11 titlestylist learning to generate headlines with controlled styles github 72 stars nlp research reproducibility a systematic review of reproducibility research in natural language processing https arxiv org abs 2103 07929 paper march 2021 license cc0 license attributions resources all linked resources belong to original authors icons akropolis https thenounproject com search q ancient 20greek i 403786 by parkjisun from the noun project https thenounproject com book https thenounproject com icon 304884 of ester by gilad sotil from the noun project https thenounproject com quill https thenounproject com term quill 17013 by juan pablo bravo from the noun project https thenounproject com acting https thenounproject com term acting 2369397 by flatart from the noun project https thenounproject com olympic https thenounproject com term olympic 1870751 by supalerk laipawat from the noun project https thenounproject com aristocracy https thenounproject com eucalyp collection ancient greece line i 3156156 by eucalyp from the noun project https thenounproject com horn https thenounproject com eucalyp collection ancient greece line i 3156640 by eucalyp from the noun project https thenounproject com temple https thenounproject com eucalyp collection ancient greece line i 3156638 by eucalyp from the noun project https thenounproject com constellation https thenounproject com eucalyp collection ancient greece glyph i 3156142 by eucalyp from the noun project https thenounproject com ancient greek round pattern https thenounproject com term ancient greek round pattern 2048889 by olena panasovska from the noun project https thenounproject com harp by vectors point from the noun project https thenounproject com atlas https thenounproject com naripuru collection ancient gods i 2225785 by parkjisun from the noun project https thenounproject com parthenon https thenounproject com eucalyp collection ancient greece line i 3158942 by eucalyp from the noun project https thenounproject com papyrus https thenounproject com iconmark collection greek mythology i 3515982 by iconmark from the noun project https thenounproject com papyrus https thenounproject com search q papyrus i 2239368 by smalllike from the noun project https thenounproject com pegasus https thenounproject com search q pegasus i 2266449 by saeful muslim from the noun project https thenounproject com fonts dalek font https www dafont com dalek font h3 align center the pandect series also includes h3 p align middle a href https github com ivan bilan the microservices pandect img src https raw githubusercontent com ivan bilan the engineering manager pandect main resources images microservices pandect promo png width 390 a nbsp nbsp nbsp a href https github com ivan bilan the engineering manager pandect img src https raw githubusercontent com ivan bilan the engineering manager pandect main resources images em pandect promo png width 370 a p | nlp naturallanguageprocessing awesome-list deeplearning natural-language-processing pandect | ai |
ECE4180FinalProject | self balancing robot ece 4180 final project introduction this is a wikipage for the final project of gatech ece 4180 embedded systems design the goal of this project is to design and implement a self balancing robot using two stepper motors an mbed microcontroller and a lithium ion battery the robot will be able to balance itself on two wheels and move forward and backward team members euijun chung sai kit tang hyemin lee wiki check out our wiki page wiki https github com ejchung0406 ece4180finalproject wiki demo video the final demo video link is right here https youtu be v6smpkwjaaq | os |
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Databases_and_SQL_for_Data_Science_with_Python | databases and sql for data science with python this is a repository containing hands on labs and exercises from databases and sql for data science with python course a part of coursera ibm data engineering professional certificate | server |
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azure-iot-samples-csharp | all samples have been moved https github com azure azure iot sdk csharp samples to the main azure iot sdk for c https github com azure azure iot sdk csharp repository | server |
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frontend-challenge | pr requisitos o que permitido es6 linters no geral tanto para js como para css task runners build tools como webpack gulp grunt e afins o que n o permitido frameworks de js no geral react vue angular ember e afins bibliotecas de utilidades underscore lodash e afins frameworks bibliotecas css bootstrap foundation materializecss e afins voc pode utilizar qualquer metodologia de arquitetura de c digo se preferir o uso de sass scss liberado contanto que seu uso seja justific vel o uso de ferramentas de teste liberado jest jasmine mocha chai sinon supertest o objetivo desse teste avaliar organiza o sem ntica funcionamento e usabilidade uso e abuso das features das linguagens html css e js uso de patterns performance do c digo testes de javascript teste voc precisar criar um servidor em node js pra servir o fields json que est na raiz do projeto como uma api se preferir o uso do express permitido o formul rio a ser renderizado o de pedidos da forma que exibido aqui https www getninjas com br moda e beleza cabeleireiros atrav s do fields json voc precisar montar os campos na view informa es adicionais necess rio exibir a mensagem este campo requerido para os marcados como required true campos do tipo enumerable s o select o formul rio n o precisa fazer post temos uma cultura de testes unit rios e de integra o uma dessas formas pelo menos essencial pra esse teste se quiser fa a uma rota no node js pra exibir o formul rio num html | getninjas front-end | front_end |
Django-Shenkar-Mentoring | shenkar mentoring as part of web and cloud engineering course i have built a web application which coordinates between mentors and students br for more info about student mentor permissions click here https github com sagichubok shenkar mentoring blob master assets user 20permissions pdf br languages python javascript html css br br https shenkarmentoring pythonanywhere com mentor view img src assets mentor view gif raw true student view img src https i imgur com x3krkad gif | cloud |
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e6156examples | e6156examples some simple examples of how to use various technologies in the e6156 topics in sw engineering cloud computing class | cloud |
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trampoline | trampoline trampoline is a static rtos for small embedded systems its api is aligned with osek vdx os and autosar os 4 2 standards 8 platforms are supported by now cortex cortex m m0 m3 and m4 for now instruction set cortex a a7 instruction set this port is under heavy development riscv pulpino microprocessor with 32bits risc v instruction set ppc powerpc 32bits instruction set posix virtual platform for posix systems tested on linux and os x avr avr 8 bits microcontrollers arm arm 32 bits instruction set virt v7 cortex a9 cortex a7 virtualized instruction set this port is used with the hypervisor xvisor msp430 cpux which has been developed on msp430fr5969 and msp430fr5994 microcontrollers and we welcome external contributors to extend this list trampoline runs on the following platforms mcu architecture cores evaluation board atmel atmega328p 8 bit avr 1 arduino uno atmel atmega2560 8 bit avr 1 arduino mega atmel sam d21 cortex m0 1 xplainedpro broadcom bcm2836 cortex a7 4 raspberry pi 2 model b nxp lpc2294 arm7 1 olimex lpc l2294 1mb nxp freescale mk20dx256 cortex m4 1 teensy31 nxp freescale mpc564xl power architecture 2 xpc56xx evb xpc56xl mini module pulpino risc v 1 zedboard stmicroelectronics stm32f4xx cortex m4 1 stm32f4discovery with stm32f407vg stmicroelectronics stm32f30x cortex m4 1 nucleo 32 stm32f303k8 stmicroelectronics stm32l432 cortex m4 1 nucleo 32 stm32l432kc microsemi smartfusion2 cortex m3 1 starterkit msp430fr5969 msp430fr5994 cpux 1 launchpad msp exp430fr5969 launchpad msp exp430fr5994 some examples are available check examples cortex m4 with c stm32f407 cortex armv7em stm32f407 stf32f4discovery blink blinks a led using an alarm and a task readbutton the example polls the button to start an alarm that activates a task to blink a led readbutton isr same but the button triggers an isr alarms it is the same example than readbutton isr but we test the return value of setrelalarm for return parameters when in kernel system call mode timer isr2 trigered by timer tim2 cortex m4 with mcu stm32f303k8 cortex armv7em stm32f303 nucleo 32 there are few differences from the stm32f407 target and examples should be easily imported blink blinks a led using an alarm and a task cortex m4 with mcu stm32l432kc cortex armv7em stm32l432 nucleo 32 blink blinks a led using an alarm and a task readbutton the example polls the button to start an alarm that activates a task to blink a led readbutton isr same but the button triggers an isr cortex m4 with c mk20dx256 cortex armv7em mk20dx256 teensy31 blink blinks the teensy 3 1 led using an alarm and a task startstopblink the example polls a button connected to pin 8 to start an alarm that activates a task to blink a led liquidcrystal startstopblink extended in addition the periodic task prints a value on a lcd isr2onpit use the pit channel 0 to trigger an isr2 isr1onftm use the ftm0 to trigger an isr1 and generate a variable width pulse cortex m3 with c smartfusion2 cortex armv7m smartfusion2 blink a simple periodic example which toggles the two green leds ds3 ds4 of the board fpgainterrupt an interrupt from the fpga fabriq toggles the green led ds4 of the board and a periodic task blinks another led cortex m0 with c samd21 cortex armv6m samd21 xplainedpro blink blinks a led using an alarm and a task readbutton the example polls the button to start an alarm that activates a task to blink a led readbutton isr same but the button triggers an isr cortex a7 with bcm2836 raspberry pi 2 cortex a armv7 bcm2836 rpi2 blink a first runable blink example is available we need a bootloader and and a console this stuff will be soon available as well single core for the moment avr 3 examples for arduino uno atmega328p chip and arduino mega atmega2560 chip blink blinks a led using an alarm and a task serial improve blink use the standard arduino serial api extinterrupt improve serial add 2 isrs to change the alarm period arm 1 example for olimex lpc2294 board lonely blinks a led 3 tasks isr category 1 or 2 counts interrupts from the push button ppc 5 examples for mpc5643l blink 1c blinks a led using an alarm and a task blink 1c withorti blinks a led using an alarm and a task creates an orti file blink 2c blinks two leds using two synchronized cores with one task and one alarm per core blink 2c arxml same as the two cores blink example but uses an arxml config file blink 2c opticks same as the two cores blink example but optimizes ticks button 2c waits for a button input to light a led switch it off using timing protection watchdog multicore example spinlocks producer consumer example pulpino riscv pulpino blink has two tasks who alternate outputting on uart interface virt v7 firmware builds a firmware that can be used as a guest on xvisor msp430 cpux 4 examples for launchpad msp exp430fr5969 and for msp exp430fr5994 blink blink led2 with a 100ms period readbutton blink led2 with a 200ms period button s1 allows to start and stop the blinking readbutton isr1 blink led2 with a 200ms period button s1 triggers an isr1 that swtches led1 readbutton isr2 blink led2 with a 200ms period button s1 triggers an isr2 that swtches led1 more examples are coming precompiled binaries of goil the oil and arxml compiler updated to version 3 1 12 on 2020 november 2 linux 32 bits goil linux 32 zip http osek triskell org goil linux 32 zip linux 64 bits goil linux 64 zip http osek triskell org goil linux 64 zip windows goil windows zip http osek triskell org goil windows zip mac os x intel goil mac os x zip http osek triskell org goil mac os x zip mac os x silicon goil mac os x silicon zip http osek triskell org goil mac os x silicon zip mac os x cocoa application with editor intel cocoagoil app zip http osek triskell org cocoagoil app zip mac os x cocoa application with editor silicon cocoagoil silicon app zip http osek triskell org cocoagoil silicon app zip note goil binaries for mac os x are not signed you can either recompile goil rom sources script in goil makefile macosx or self sign the binary information here https stackoverflow com questions 58356844 what are the ways or technologies to sign an executable application file in mac useful links arm development tools https developer arm com tools and software open source software developer tools gnu toolchain gnu rm compiled for various platforms the osek vdx portal is down since at least june 2017 because the working group has been disbanded in favor of autosar here are copies of a part of the documents that were available for download oil specification http osek triskell org oil25 pdf os specification http osek triskell org os223 pdf com specification http osek triskell org osekcom303 pdf orti a http osek triskell org orti a 22 pdf and orti b http osek triskell org orti b 22 pdf specifications os test plan http osek triskell org ostestplan20 pdf os test procedure http osek triskell org ostestproc20 pdf com test plan http osek triskell org comtestplan20 pdf com test procedure http osek triskell org comtestproc20 pdf | autosar rtos osek-vdx trampoline | os |
TECE-Team-4 | tece team 4 booz allen tech excellence cloud engineering team 4 | cloud |
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iot | https github com azure iot workflows markdown 20links badge svg awesome azure iot a curated list of awesome azure iot projects and resources iot solutions azure iot central https github com azure iot central azure iot central is azure s application as a platform apaas solution for connecting and managing devices at scale enabling customers to spend their time energy and budget using iot data to create business value rather than simply getting iot data iot services azure iot hub https docs microsoft com azure iot hub connect monitor and manage billions of iot assets azure iot hub is a fully managed service that enables reliable and secure bidirectional communications between millions of iot devices and a solution back end azure iot hub device provisioning service https docs microsoft com azure iot dps seamless zero touch registration of devices to iot hub with security that begins at the device and ends with our cloud azure event hubs https docs microsoft com azure event hubs cloud scale telemetry ingestion from websites apps and any streams of data azure stream analytics https docs microsoft com azure stream analytics real time data stream processing from millions of iot devices azure time series insights https docs microsoft com azure time series insights a fully managed analytics storage and visualization service that makes it simple to explore and analyze billions of iot events simultaneously sdks azure sdk for embedded c https github com azure azure iot sdk c designed to allow small embedded iot devices to communicate with azure services azure iot middleware for azure rtos https github com azure rtos netxduo tree master addons azure iot a platform specific library that acts as a binding layer between the azure rtos and the azure sdk for embedded c azure iot middleware for freertos https github com azure azure iot middleware freertos a platform specific library that acts as a binding layer between the freertos and the azure sdk for embedded c azure iot device sdk for net https github com azure azure iot sdk csharp repository for the net sdks packages are also published on nuget azure iot device sdk for java https github com azure azure iot sdk java repository for the java sdks packages are also published on maven azure iot device sdk for node js https github com azure azure iot sdk node repository for the node sdks packages are also published on npm azure iot device sdk for python https github com azure azure iot sdk python repository for the python sdks packages are also published on pip iot device development iot device development https docs microsoft com azure iot develop explore the azure iot documentation for developing cloud connected embedded devices and device applications choosing an device sdk https docs microsoft com azure iot develop about iot sdks device or service sdks embedded or higher order getting started with azure rtos https github com azure rtos getting started connect a range of popular devkits from our silicon vendor parts to azure iot in under 30 minutes azure device certification https certify azure com certify your devices for one or more of our certifications and publish them to the iot device catalog azure certified device catalog https devicecatalog azure com browse certified for iot devices tailored to your needs platforms and frameworks azure iot edge https docs microsoft com azure iot edge azure iot edge moves cloud analytics and custom business logic to devices so that your organization can focus on business insights instead of data management azure industrial iot https github com azure industrial iot azure industrial iot platform includes components and services to connect industrial equipment to azure it can be used to build applications that can monitor and manage factory operations libraries and tools azure iot cli https docs microsoft com cli azure iot view azure cli latest commands to connect monitor and control azure iot hub service azure iot explorer https github com azure azure iot explorer a graphical tool for interacting with and devices connected to your iot hub azure iot edge for visual studio code https marketplace visualstudio com items itemname vsciot vscode azure iot edge develop deploy debug and manage your iot edge solution azure iot toolkit for visual studio code https marketplace visualstudio com items itemname vsciot vscode azure iot toolkit interact with azure iot hub iot device management iot hub code snippets azure iot web client https azure iot github io a web based client tool for azure iot hub to send and monitor device to cloud messages iot hub rest api https docs microsoft com rest api iothub the rest apis for iot hub offer programmatic access to the device and messaging services as well as the resource provider in iot hub learning material azure iot learn https docs microsoft com learn browse products azure iot tutorials and getting started material microsoft professional program for internet of things iot https academy microsoft com professional program tracks internet of things professional course for iot offered by microsoft microsoft learn https docs microsoft com learn browse term iot tutorials and learning paths resources azure iot reference architecture https docs microsoft com azure architecture reference architectures iot reference architecture shows a recommended architecture for iot applications on azure using paas platform as a service components azure blog for internet of things https azure microsoft com blog topics internet of things the official microsoft azure blog for topics about internet of things iot developer blog https blogs msdn microsoft com iotdev msdn blog about tooling and experience for iot developer channel 9 iot show https aka ms iotshow series of videos for developers covering iot at microsoft | server |
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bearingpoint-internship-2018 | img src https www bearingpoint com files brp logo rgb ps jpg download true width 300px bearingpoint internship 2018 a simple task manager application written at the software engineering training organized by bearingpoint database design java maven git trello slack in a team of 6 students | java web | server |
pigment | pigment p a href license md img src https img shields io github license kobaltedev pigment alt mit license a a href https www npmjs com package kobalte pigment img src https img shields io npm v kobalte pigment alt npm kobalte pigment a a href https www npmjs com package kobalte pigment img src https img shields io npm dm kobalte pigment svg alt npm downloads height 18 a p warning pigment is not available yet on npm an open source design system for building solidjs application documentation for full documentation visit pigment kobalte dev https pigment kobalte dev acknowledgment atlassian design system https atlassian design nord design system https nordhealth design joy ui https mui com joy ui getting started overview license this project is licensed under the mit license | design-system kobalte solidjs component-library tailwindcss | os |
IHSAINCIOS | ihsainc ios the ios group for software engineering ihsainc project https discord gg xzn2nbqz br milestone documentation link https docs google com document d 1y9lamhpoyoreezvaw8ha4hxncv93c0qbnrkwgt3 les edit | os |
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shopping-ui-service | shoppinguiservice this project was generated with angular cli https github com angular angular cli version 1 0 0 beta 19 3 dependencies xslt nodejs v6 9 1 npm 3 10 8 installation sudo npm i angular g git clone https github com knguyen6 shopping ui service git cd shopping ui service npm i how to run the app in development mode xslt ng serve navigate to http localhost 4200 the app will automatically reload if you change any of the source files how to run the app in production xslt npm start code scaffolding run ng generate component component name to generate a new component you can also use ng generate directive pipe service class build run ng build to build the project the build artifacts will be stored in the dist directory use the prod flag for a production build running unit tests run ng test to execute the unit tests via karma https karma runner github io running end to end tests run ng e2e to execute the end to end tests via protractor http www protractortest org before running the tests make sure you are serving the app via ng serve deploying to github pages run ng github pages deploy to deploy to github pages further help to get more help on the angular cli use ng help or go check out the angular cli readme https github com angular angular cli blob master readme md reference setup materialize css just skip the part of including materialize css in angular cli build js file we don t need to to that https medium com ladyleet using materializecss with your angular 2 angular cli app 2eb64b05a1d2 9zweqzhuo | cloud |
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uxm | p align center img src github logo png p p align center an utility library for collecting user centric performance metrics p p align center a href why a a href usage usage a a href api api a a href credits credits a p br br features modular design based on es modules small size 2 5kb gzip it s usually smaller when you use a few features and tree shaking https webpack js org guides tree shaking graceful support of latest browser apis like performance paint timing https developer mozilla org en us docs web api performancepainttiming network information https wicg github io netinfo or device memory https w3c github io device memory fully featured user timing api v3 https developer mozilla org en us docs web api user timing api support usage https img shields io npm v uxm svg https npmjs org package uxm https img shields io badge license mit blue svg license bash npm install uxm next collect user centric metrics https web dev metrics and send data to your api 1 5kb js import collectmetrics createapireporter getdeviceinfo from uxm const report createapireporter api collect initial getdeviceinfo collectmetrics fcp lcp fid cls metrictype value report metrictype value at the end of the session on visibilitychange event your api receives a post request using sendbeacon with data for core ux metrics and a device information like json fcp 1409 fid 64 lcp 2690 cls 0 025 url https example com memory 8 cpus 2 connection effectivetype 4g rtt 150 downlink 4 25 explore examples for building a robust real user monitoring rum logic size of each example is controlled using size limit package json l74 details summary report fcp and fid to google analytics 0 7 kb summary use google analytics as a free rum service and report user centric performance metrics learn more about using google analytics for site speed monitoring https philipwalton com articles the google analytics setup i use on every site i build performance tracking google analytics reporter js examples google analytics reporter js js import collectfcp collectfid from uxm collectfcp reporttogoogleanalytics collectfid reporttogoogleanalytics function reporttogoogleanalytics metric ga send event eventcategory performance metrics eventaction track metric metrictype metric value details details summary measure react view render performance 0 65 kb summary a react hook example that measures rendering performance and creates a custom user timing https developer mozilla org en us docs web api user timing api measure react use time hook js examples react use time hook js js import time timeendpaint from uxm export function app usetime render app return hello from react function usetime label time label render started useeffect timeendpaint label render ended and the browser paint has been procceed details details summary build a custom layout shift metric for spa 0 8 kb summary layout instability https wicg github io layout instability is a flexible api that allows building custom metrics on top like measuring cumulative layout shift per view not the whole session custom layout shift js examples custom layout shift js js import observeentries from uxm import observehistory from uxm experimental type url string cls number let views let cls 0 cummulate layout shift values with an input observeentries layout shift layoutshiftentries layoutshiftentries foreach e if e hadrecentinput cls e value observe history changes and reset cls when a route changes observehistory e views push url e prevurl cls cls 0 details details summary collect crux like metrics 1 6kb summary chrome ux report crux https developers google com web tools chrome user experience report is a great way to see how real world chrome users experience the speed of your website but for privacy reasons crux aggregates data only per origin this script collects detailed crux like analytics on the url level crux metrics js examples crux metrics js js import getdeviceinfo collectload collectfcp collectlcp collectfid collectcls onvisibilitychange from uxm init metrics and get device information const connection url getdeviceinfo const metrics url effectiveconnectiontype connection effectivetype collect loading metrics collectload value load detail domcontentloaded timetofirstbyte metrics timetofirstbyte timetofirstbyte metrics domcontentloaded domcontentloaded metrics load load collect user centric metrics collectfcp value metrics firstcontentfulpaint value collectlcp value metrics largestcontentfulpaint value collectfid value metrics firstinputdelay value collectcls value metrics cumulativelayoutshift value all metrics are collected on visibilitychange event onvisibilitychange console log metrics url https example com effectiveconnectiontype 4g timetofirstbyte 1204 domcontentloaded 1698 load 2508 firstcontentfulpaint 1646 largestcontentfulpaint 3420 firstinputdelay 12 cumulativelayoutshift 0 12 1 details api metrics metrics collectmetrics metrics callback collectmetricsmetrics callback collectfcp callback collectfcpcallback collectfid callback collectfidcallback collectlcp callback options collectlcpcallback options collectcls callback options collectclscallback options collectload callback collectloadcallback performance observer performance observer observeentries options callback getentriesbytype entrytype onvisibilitychange callback onload callback reporter reporter createapireporter url options getdeviceinfo user timing user timing mark markname markoptions measure markname startormeasureoptions endmarkname time label startlabel timeend label startlabel timeendpaint label startlabel now experimental alpha experimental alpha collectcid callback observehistory callback recordtrace callback options calcspeedscore values ranks metrics metrics are the core of uxm uxm is a 3 letter acronym that stands for user experience metrics it focuses on metrics that captures a user experience instead of measuring technical details that are easy to manipulate this metrics are more representetive for a user and the final purpose of a good frontend is to create a delightful user experience each metric follows the structure metrictype string a metric acronym ex lcp fid or cls value number a numeric value of a metric ex 1804 for lcp 4 for fid or 0 129 for cls detail object an extra detail specific for an each metric like elementselector for lcp event name for fid or totalentries for cls with an exception for collectload it does not have a 3 letters acronym and considered a legacy use a per metric function for more granular control of the callback behavior and saving a bundle size this metrics are only available in chromium based browsers chrome edge opera the best way to understand a metric is to read web dev metrics and check the source src metrics js collectmetrics metrics callback metrics array string object callback function the method is a shortcut for calling collectfcp collectfcpcallback collectfid collectfidcallback collectlcp collectlcpcallback options and collectcls collectclscallback options js import collectmetrics from uxm const report createapireporter api collect pass a metric 3 letter acronym collectmetrics fcp fid metric report metric metrictype metric value or a metric options using an object and type collectmetrics type lcp maxtimeout 1000 metric report lcp metric value collectfcp callback callback function a callback with fcpmetric metrictype fcp value number a time when the user can see anything on the screen a fast fcp helps reassure the user that something is happening collect first contentful paint fcp https web dev fcp using paint https www w3 org tr paint timing entries collectfid callback callback function a callback with fidmetric metrictype fid value number detail object name string duration number starttime number processingstart number processingend number js import collectfid from uxm collectfid metric console log metric metrictype fid value 1 detail duration 8 starttime 2568 1 processingstart 2568 99 processingend 2569 02 name mousedown collectlcp callback options callback function a callback with lcpmetric metrictype lcp value number a time when the page s main content has likely loaded a fast lcp helps reassure the user that the page is useful detail object elementselector string css selector of an element that is triggered the most significant paint size number size height x width of the largest element options object optional maxtimeout number the longest delay between largest contentful paint entries to consider the lcp defaults to 10000 ms collect largest contentful paint lcp https web dev lcp using largest contentful paint https wicg github io largest contentful paint entries a callback triggers when a user interacts with a page or after maxtimeout between entries or on visibilitychange event js import collectlcp from uxm collectlcp metric console log metric metrictype lcp value 2450 detail size 8620 elementselector body h1 collectcls callback options callback function a callback with clsmetric metrictype cls value number detail object totalentries number sessionduration number js import collectcls from uxm collectcls metric console log metric metrictype cls value 0 0893 detail totalentries 2 sessionduration 2417 maxtimeout 1000 collectload callback callback function a callback with clsmetric metrictype load value number detail object timetofirstbyte number domcontentloaded number js import collectload from uxm collectload value load detail domcontentloaded timetofirstbyte console log timetofirstbyte domcontentloaded load performance observer observeentries options callback getentriesbytype entrytype reporter createapireporter url options user timing mark markname markoptions measure markname startormeasureoptions endmarkname time label startlabel timeend label startlabel timeendpaint label startlabel now device info getdeviceinfo experimental alpha collectcid callback observehistory callback recordtrace callback options calcspeedscore values ranks credits made with by treo https treo sh array https developer mozilla org en us docs web javascript reference global objects array array function https developer mozilla org en us docs web javascript reference global objects function function number https developer mozilla org en us docs web javascript data structures number type number object https developer mozilla org en us docs web javascript reference global objects object object | web-performance real-user-monitoring user-experience user-centric-metrics | front_end |
awesome-production-machine-learning | awesome images awesome svg https github com sindresorhus awesome maintenance https img shields io badge maintained 3f yes green svg https github com ethicalml awesome production machine learning graphs commit activity github https img shields io badge release prod yellow svg github https img shields io badge languages multi blue svg github https img shields io badge license mit lightgrey svg github https img shields io twitter follow axsaucedo svg label follow https twitter com axsaucedo awesome production machine learning this repository contains a curated list of awesome open source libraries that will help you deploy monitor version scale and secure your production machine learning quick links to sections in this page explaining predictions models explaining black box models and datasets privacy preserving ml privacy preserving ml model data versioning model and data versioning model training orchestration model training orchestration model serving monitoring model serving and monitoring automl automl data pipeline data pipeline data labelling data labelling metadata management metadata management computation distribution computation load distribution model serialisation model serialisation optimized computation optimized computation data stream processing data stream processing red circle outlier anomaly detection outlier and anomaly detection feature store feature store adversarial robustness adversarial robustness data storage optimization data storage optimisation data science notebook data science notebook neural search neural search industry strength computer vision industry strength cv industry strength natural language processing industry strength nlp industry strength reinforcement learning industry strength rl industry strength visualisation industry strength visualisation industry strength recommender system industry strength recsys industry strength benchmarking evaluation industry strength benchmarking and evaluation commercial platform commercial platform 10 min video overview table tr td width 30 this a href https www youtube com watch v ynb6x0kzkxy 10 minute video a provides an overview of the motivations for machine learning operations as well as a high level overview on some of the tools in this repo this a href https www youtube com watch v xymbp8rwacq t 1s newer video a covers the an updated 2022 version of the state of mlops td td width 70 a href https www youtube com watch v ynb6x0kzkxy img src images video png a td tr table want to receive recurrent updates on this repo and other advancements table tr td width 30 you can join the a href https ethical institute mle html machine learning engineer a newsletter join over 10 000 ml professionals and enthusiasts who receive weekly curated articles tutorials on production machine learning td td width 70 a href https ethical institute mle html img src images mleng png a td tr tr td width 30 also check out the a href https github com ethicalml awesome artificial intelligence guidelines awesome artificial intelligence guidelines a list where we aim to map the landscape of frameworks codes of ethics guidelines regulations etc related to artificial intelligence td td width 70 a href https github com ethicalml awesome artificial intelligence guidelines img src images guidelines jpg a td tr table main content explaining black box models and datasets aequitas https github com dssg aequitas https img shields io github stars dssg aequitas svg style social an open source bias audit toolkit for data scientists machine learning researchers and policymakers to audit machine learning models for discrimination and bias and to make informed and equitable decisions around developing and deploying predictive risk assessment tools ai explainability 360 https github com trusted ai aix360 https img shields io github stars trusted ai aix360 svg style social interpretability and explainability of data and machine learning models including a comprehensive set of algorithms that cover different dimensions of explanations along with proxy explainability metrics ai fairness 360 https github com trusted ai aif360 https img shields io github stars trusted ai aif360 svg style social a comprehensive set of fairness metrics for datasets and machine learning models explanations for these metrics and algorithms to mitigate bias in datasets and models alibi https github com seldonio alibi https img shields io github stars seldonio alibi svg style social alibi is an open source python library aimed at machine learning model inspection and interpretation the initial focus on the library is on black box instance based model explanations anchor https github com marcotcr anchor https img shields io github stars marcotcr anchor svg style social code for the paper high precision model agnostic explanations https homes cs washington edu marcotcr aaai18 pdf a model agnostic system that explains the behaviour of complex models with high precision rules called anchors captum https github com pytorch captum https img shields io github stars pytorch captum svg style social model interpretability and understanding library for pytorch developed by facebook it contains general purpose implementations of integrated gradients saliency maps smoothgrad vargrad and others for pytorch models casme https github com kondiz casme https img shields io github stars kondiz casme svg style social example of using classifier agnostic saliency map extraction on imagenet presented on the paper classifier agnostic saliency map extraction https arxiv org abs 1805 08249 cleverhans https github com tensorflow cleverhans https img shields io github stars tensorflow cleverhans svg style social an adversarial example library for constructing attacks building defenses and benchmarking both a python library to benchmark system s vulnerability to adversarial examples http karpathy github io 2015 03 30 breaking convnets contrastiveexplanation foil trees https github com marcelrobeer contrastiveexplanation https img shields io github stars marcelrobeer contrastiveexplanation svg style social python script for model agnostic contrastive counterfactual explanations for machine learning accompanying code for the paper contrastive explanations with local foil trees https arxiv org abs 1806 07470 deeplift https github com kundajelab deeplift https img shields io github stars kundajelab deeplift svg style social codebase that contains the methods in the paper learning important features through propagating activation differences https arxiv org abs 1704 02685 here is the slides https docs google com file d 0b15f qn41vqxsxrfmzgts01uou0 edit filetype mspresentation and the video https vimeo com 238275076 of the 15 minute talk given at icml deepvis toolbox https github com yosinski deep visualization toolbox https img shields io github stars yosinski deep visualization toolbox svg style social this is the code required to run the deep visualization toolbox as well as to generate the neuron by neuron visualizations using regularized optimization the toolbox and methods are described casually here http yosinski com deepvis and more formally in this paper https arxiv org abs 1506 06579 eli5 https github com teamhg memex eli5 https img shields io github stars teamhg memex eli5 svg style social explain like i m 5 is a python package which helps to debug machine learning classifiers and explain their predictions facets https github com pair code facets https img shields io github stars pair code facets svg style social facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets get a sense of the shape of each feature of your dataset using facets overview or explore individual observations using facets dive fairlearn https github com fairlearn fairlearn https img shields io github stars fairlearn fairlearn svg style social fairlearn is a python toolkit to assess and mitigate unfairness in machine learning models fairml https github com adebayoj fairml https img shields io github stars adebayoj fairml svg style social fairml is a python toolbox auditing the machine learning models for bias fairness comparison https github com algofairness fairness comparison https img shields io github stars algofairness fairness comparison svg style social this repository is meant to facilitate the benchmarking of fairness aware machine learning algorithms based on this paper https arxiv org abs 1802 04422 fairness indicators https github com tensorflow fairness indicators https img shields io github stars tensorflow fairness indicators svg style social the tool supports teams in evaluating improving and comparing models for fairness concerns in partnership with the broader tensorflow toolkit gebi global explanations for bias identification https github com agamiko gebi https img shields io github stars agamiko gebi svg style social an attention based summarized post hoc explanations for detection and identification of bias in data we propose a global explanation and introduce a step by step framework on how to detect and test bias python package for image data innvestigate https github com albermax innvestigate https img shields io github stars albermax innvestigate svg style social an open source library for analyzing keras models visually by methods such as deeptaylor decomposition https www sciencedirect com science article pii s0031320316303582 patternnet https openreview net forum id hkn7cbatw saliency maps https arxiv org abs 1312 6034 and integrated gradients https arxiv org abs 1703 01365 integrated gradients https github com ankurtaly integrated gradients https img shields io github stars ankurtaly integrated gradients svg style social this repository provides code for implementing integrated gradients for networks with image inputs interpretml https github com interpretml interpret https img shields io github stars interpretml interpret svg style social interpretml is an open source package for training interpretable models and explaining blackbox systems keras vis https github com raghakot keras vis https img shields io github stars raghakot keras vis svg style social keras vis is a high level toolkit for visualizing and debugging your trained keras neural net models currently supported visualizations include activation maximization saliency maps class activation maps l2x https github com jianbo lab l2x https img shields io github stars jianbo lab l2x svg style social code for replicating the experiments in the paper learning to explain an information theoretic perspective on model interpretation https arxiv org pdf 1802 07814 pdf at icml 2018 lightly https github com lightly ai lightly https img shields io github stars lightly ai lightly svg style social a python framework for self supervised learning on images the learned representations can be used to analyze the distribution in unlabeled data and rebalance datasets lightwood https github com mindsdb lightwood https img shields io github stars mindsdb lightwood svg style social a pytorch based framework that breaks down machine learning problems into smaller blocks that can be glued together seamlessly with an objective to build predictive models with one line of code lime https github com marcotcr lime https img shields io github stars marcotcr lime svg style social local interpretable model agnostic explanations for machine learning models lofo importance https github com aerdem4 lofo importance https img shields io github stars aerdem4 lofo importance svg style social lofo leave one feature out importance calculates the importances of a set of features based on a metric of choice for a model of choice by iteratively removing each feature from the set and evaluating the performance of the model with a validation scheme of choice based on the chosen metric mindsdb https github com mindsdb mindsdb https img shields io github stars mindsdb mindsdb svg style social mindsdb is an explainable automl framework for developers with mindsdb you can build train and use state of the art ml models in as simple as one line of code mljar supervised https github com mljar mljar supervised https img shields io github stars mljar mljar supervised svg style social a python package for automl on tabular data with feature engineering hyper parameters tuning explanations and automatic documentation netron https github com lutzroeder netron https img shields io github stars lutzroeder netron svg style social viewer for neural network deep learning and machine learning models pybreakdown https github com mi2datalab pybreakdown https img shields io github stars mi2datalab pybreakdown svg style social a model agnostic tool for decomposition of predictions from black boxes break down table shows contributions of every variable to a final prediction responsibly https github com responsiblyai responsibly https img shields io github stars responsiblyai responsibly svg style social toolkit for auditing and mitigating bias and fairness of machine learning systems shap https github com slundberg shap https img shields io github stars slundberg shap svg style social shapley additive explanations is a unified approach to explain the output of any machine learning model shapash https github com maif shapash https img shields io github stars maif shapash svg style social shapash is a python library that provides several types of visualization that display explicit labels that everyone can understand skater https github com datascienceinc skater https img shields io github stars datascienceinc skater svg style social skater is a unified framework to enable model interpretation for all forms of model to help one build an interpretable machine learning system often needed for real world use cases tensorflow s model analysis https github com tensorflow model analysis https img shields io github stars tensorflow model analysis svg style social tensorflow model analysis tfma is a library for evaluating tensorflow models it allows users to evaluate their models on large amounts of data in a distributed manner using the same metrics defined in their trainer themis ml https github com cosmicbboy themis ml https img shields io github stars cosmicbboy themis ml svg style social themis ml is a python library built on top of pandas and sklearn that implements fairness aware machine learning algorithms themis https github com laser umass themis https img shields io github stars laser umass themis svg style social themis is a testing based approach for measuring discrimination in a software system treeinterpreter https github com andosa treeinterpreter https img shields io github stars andosa treeinterpreter svg style social package for interpreting scikit learn s decision tree and random forest predictions allows decomposing each prediction into bias and feature contribution components as described here http blog datadive net interpreting random forests whatif https github com pair code what if tool https img shields io github stars pair code what if tool svg style social an easy to use interface for expanding understanding of a black box classification or regression ml model woe https github com boredbird woe https img shields io github stars boredbird woe svg style social tools for woe transformation mostly used in scorecard model for credit rating xai explainableai https github com ethicalml xai https img shields io github stars ethicalml xai svg style social an explainability toolbox for machine learning privacy preserving ml bastionlab https github com mithril security bastionlab https img shields io github stars mithril security bastionlab svg style social bastionlab is a framework for confidential data science collaboration it uses confidential computing access control data science and differential privacy to enable data scientists to remotely perform data exploration statistics and training on confidential data while ensuring maximal privacy for data owners concrete ml https github com zama ai concrete ml https img shields io github stars zama ai concrete ml svg style social concrete ml is a privacy preserving machine learning ppml open source set of tools built on top of the concrete framework by zama https github com zama ai it aims to simplify the use of fully homomorphic encryption fhe for data scientists to help them automatically turn machine learning models into their homomorphic equivalent concrete ml https github com bytedance fedlearner https img shields io github stars bytedance fedlearner svg style social fedlearner is collaborative machine learning framework that enables joint modeling of data distributed between institutions fate https github com federatedai fate https img shields io github stars federatedai fate svg style social fate federated ai technology enabler is the world s first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy fedml https github com fedml ai fedml https img shields io github stars fedml ai fedml svg style social fedml provides a research and production integrated edge cloud platform for federated distributed machine learning at anywhere at any scale flower https github com adap flower https img shields io github stars adap flower svg style social flower is a federated learning framework with a unified approach it enables the federation of any ml workload with any ml framework and any programming language google s differential privacy https github com google differential privacy https img shields io github stars google differential privacy svg style social this is a c library of differentially private algorithms which can be used to produce aggregate statistics over numeric data sets containing private or sensitive information intel homomorphic encryption backend https github com nervanasystems he transformer https img shields io github stars nervanasystems he transformer svg style social the intel he transformer for ngraph is a homomorphic encryption he backend to the intel ngraph compiler intel s graph compiler for artificial neural networks microsoft seal https github com microsoft seal https img shields io github stars microsoft seal svg style social microsoft seal is an easy to use open source mit licensed homomorphic encryption library developed by the cryptography research group at microsoft openfl https github com intel openfl https img shields io github stars intel openfl svg style social openfl is a python framework for federated learning openfl is designed to be a flexible extensible and easily learnable tool for data scientists openfl is developed by intel internet of things group iotg and intel labs pysyft https github com openmined pysyft https img shields io github stars openmined pysyft svg style social a python library for secure private deep learning pysyft decouples private data from model training using multi party computation mpc within pytorch rosetta https github com latticex foundation rosetta https img shields io github stars latticex foundation rosetta svg style social a privacy preserving framework based on tensorflow with customized backend operations using multi party computation mpc rosetta reuses the apis of tensorflow and allows to transfer original tensorflow codes into a privacy preserving manner with minimal changes substra https github com substrafoundation substra https img shields io github stars substrafoundation substra svg style social substra is an open source framework for privacy preserving traceable and collaborative machine learning tensorflow privacy https github com tensorflow privacy https img shields io github stars tensorflow privacy svg style social a python library that includes implementations of tensorflow optimizers for training machine learning models with differential privacy tf encrypted https github com tf encrypted tf encrypted https img shields io github stars tf encrypted tf encrypted svg style social a framework for confidential machine learning on encrypted data in tensorflow model and data versioning aim https github com aimhubio aim https img shields io github stars aimhubio aim style social a super easy way to record search and compare ai experiments catalyst https github com catalyst team catalyst https img shields io github stars catalyst team catalyst svg style social high level utils for pytorch dl rl research it was developed with a focus on reproducibility fast experimentation and code ideas reusing clearml https github com allegroai clearml https img shields io github stars allegroai clearml svg style social auto magical experiment manager version control for ai previously trains codalab https github com codalab codalab worksheets https img shields io github stars codalab codalab worksheets svg style social codalab worksheets is a collaborative platform for reproducible research that allows researchers to run manage and share their experiments in the cloud it helps researchers ensure that their runs are reproducible and consistent data version control dvc https github com iterative dvc https img shields io github stars iterative dvc svg style social a git fork that allows for version management of models deepkit https github com deepkit deepkit ml https img shields io github stars deepkit deepkit ml svg style social an open source platform and cross platform desktop application to execute track and debug modern machine learning experiments dolt https github com dolthub dolt https img shields io github stars dolthub dolt svg style social dolt is a sql database that you can fork clone branch merge push and pull just like a git repository flor https github com ucbrise flor https img shields io github stars ucbrise flor svg style social easy to use logger and automatic version controller made for data scientists who write ml code guild ai https github com guildai guildai https img shields io github stars guildai guildai svg style social open source toolkit that automates and optimizes machine learning experiments hangar https github com tensorwerk hangar py https img shields io github stars tensorwerk hangar py svg style social version control for tensor data git like semantics on numerical data with high speed and efficiency keepsake https github com replicate keepsake https img shields io github stars replicate keepsake svg style social version control for machine learning lakefs https github com treeverse lakefs https img shields io github stars treeverse lakefs svg style social repeatable atomic and versioned data lake on top of object storage mlflow https github com mlflow mlflow https img shields io github stars mlflow mlflow svg style social open source platform to manage the ml lifecycle including experimentation reproducibility and deployment modeldb https github com vertaai modeldb https img shields io github stars mitdbg modeldb svg style social an open source system to version machine learning models including their ingredients code data config and environment and to track ml metadata across the model lifecycle modelstore https github com operatorai modelstore https img shields io github stars operatorai modelstore svg style social an open source python library that allows you to version export and save a machine learning model to your cloud storage provider ormb https github com kleveross ormb https img shields io github stars kleveross ormb svg style social docker for your ml dl models based on oci artifacts polyaxon https github com polyaxon polyaxon https img shields io github stars polyaxon polyaxon svg style social a platform for reproducible and scalable machine learning and deep learning on kubernetes video https www youtube com watch v iexwrka hys quilt https github com quiltdata quilt https img shields io github stars quiltdata quilt svg style social versioning reproducibility and deployment of data and models sacred https github com idsia sacred https img shields io github stars idsia sacred svg style social tool to help you configure organize log and reproduce machine learning experiments studio https github com studioml studio https img shields io github stars studioml studio svg style social model management framework which minimizes the overhead involved with scheduling running monitoring and managing artifacts of your machine learning experiments terminusdb https github com terminusdb terminusdb https img shields io github stars terminusdb terminusdb svg style social a graph database management system that stores data like git model training orchestration accelerate https github com huggingface accelerate https img shields io github stars huggingface accelerate svg style social accelerate abstracts exactly and only the boilerplate code related to multi gpu tpu mixed precision and leaves the rest of your code unchanged aqueduct https github com aqueducthq aqueduct https img shields io github stars aqueducthq aqueduct svg style social aqueduct enables you to easily define run and manage ai ml tasks on any cloud infrastructure cml https github com iterative cml https img shields io github stars iterative cml svg style social continuous machine learning cml is an open source library for implementing continuous integration delivery ci cd in machine learning projects determined https github com determined ai determined https img shields io github stars determined ai determined svg style social deep learning training platform with integrated support for distributed training hyperparameter tuning and model management supports tensorflow and pytorch envd https github com tensorchord envd https img shields io github stars tensorchord envd svg style social machine learning development environment for data science and ai ml engineering teams hopsworks https github com logicalclocks hopsworks https img shields io github stars logicalclocks hopsworks svg style social hopsworks is a data intensive platform for the design and operation of machine learning pipelines that includes a feature store video https www youtube com watch v v1drny8cavu kubeflow https github com kubeflow kubeflow https img shields io github stars kubeflow kubeflow svg style social a cloud native platform for machine learning based on google s internal machine learning pipelines mleap https github com combust mleap https img shields io github stars combust mleap svg style social standardisation of pipeline and model serialization for spark tensorflow and sklearn nos https github com nebuly ai nos https img shields io github stars nebuly ai nos svg style social nos is an open source platform to efficiently run ai workloads on kubernetes increasing gpu utilization and reducing infrastructure and operational costs nvidia tensorrt https github com nvidia tensorrt https img shields io github stars nvidia tensorrt svg style social tensorrt is a c library for high performance inference on nvidia gpus and deep learning accelerators onepanel https github com onepanelio core https img shields io github stars onepanelio core style social production scale vision ai platform with fully integrated components for model building automated labeling data processing and model training pipelines open platform for ai https github com microsoft pai https img shields io github stars microsoft pai svg style social platform that provides complete ai model training and resource management capabilities pycaret https pycaret org https img shields io github stars pycaret pycaret svg style social low code library for training and deploying models scikit learn xgboost lightgbm spacy sematic https github com sematic ai sematic https img shields io github stars sematic ai sematic svg style social platform to build resource intensive pipelines with simple python skaffold https github com googlecontainertools skaffold https img shields io github stars googlecontainertools skaffold svg style social skaffold is a command line tool that facilitates continuous development for kubernetes applications you can iterate on your application source code locally then deploy to local or remote kubernetes clusters skypilot https github com skypilot org skypilot https img shields io github stars skypilot org skypilot svg style social run llms ai and batch jobs on any cloud get maximum savings highest gpu availability and managed execution all with a simple interface tensorflow extended tfx https github com tensorflow tfx https img shields io github stars tensorflow tfx svg style social production oriented configuration framework for ml based on tensorflow incl monitoring and model version management tony https github com linkedin tony https img shields io github stars linkedin tony svg style social tony is a framework to natively run deep learning jobs on apache hadoop it currently supports tensorflow pytorch mxnet and horovod zenml https github com maiot io zenml https img shields io github stars maiot io zenml svg style social zenml is an extensible open source mlops framework to create reproducible ml pipelines with a focus on automated metadata tracking caching and many integrations to other tools model serving and monitoring backprop https github com backprop ai backprop https img shields io github stars backprop ai backprop svg style social backprop makes it simple to use finetune and deploy state of the art ml models bentoml https github com bentoml bentoml https img shields io github stars bentoml bentoml svg style social bentoml is an open source framework for high performance ml model serving cortex https github com cortexlabs cortex https img shields io github stars cortexlabs cortex svg style social cortex is an open source platform for deploying machine learning models trained with any framework as production web services no devops required deepchecks https github com deepchecks deepchecks https img shields io github stars deepchecks deepchecks svg style social deepchecks is an open source package for comprehensively validating your machine learning models and data with minimal effort during development deployment or in production deepdetect https github com jolibrain deepdetect https img shields io github stars jolibrain deepdetect svg style social machine learning production server for tensorflow xgboost and cafe models written in c and maintained by jolibrain evidently https github com evidentlyai evidently https img shields io github stars evidentlyai evidently svg style social evidently helps analyze machine learning models during development validation or production monitoring the tool generates interactive reports from pandas dataframe forestflow https github com forestflow forestflow https img shields io github stars forestflow forestflow svg style social cloud native machine learning model server giskard https github com giskard ai giskard https img shields io github stars giskard ai giskard svg style social quality assurance for ai models open source platform to help organizations increase the efficiency of their ai development workflow eliminate risks of ai biases and ensure robust reliable ethical ai models helicone https github com helicone helicone https img shields io github stars helicone helicone svg style social helicone is an observability platform for llms hydrosphere ml lambda https github com hydrospheredata hydro serving https img shields io github stars hydrospheredata hydro serving svg style social open source model management cluster for deploying serving and monitoring machine learning models and ad hoc algorithms with a faas architecture jina https github com jina ai jina https img shields io github stars jina ai jina svg style social cloud native search framework that supports to use deep learning state of the art ai models for search kserve https github com kserve kserve https img shields io github stars kubeflow kfserving svg style social serverless framework to deploy and monitor machine learning models in kubernetes video https www youtube com watch v hgivlfadmhu m2cgen https github com bayeswitnesses m2cgen https img shields io github stars bayeswitnesses m2cgen svg style social a lightweight library which allows to transpile trained classic machine learning models into a native code of c java go r php dart haskell rust and many other programming languages mlem https github com iterative mlem https img shields io github stars iterative mlem svg style social version and deploy your ml models following gitops principles mlserver https github com seldonio mlserver https img shields io github stars seldonio mlserver svg style social an inference server for your machine learning models including support for multiple frameworks multi model serving and more mltrace https github com loglabs mltrace https img shields io github stars loglabs mltrace svg style social a lightweight open source python tool to get bolt on observability in ml pipelines mlwatcher https github com anodot mlwatcher https img shields io github stars anodot mlwatcher svg style social mlwatcher is a python agent that records a large variety of time serie metrics of your running ml classification algorithm it enables you to monitor in real time model server for apache mxnet mms https github com awslabs mxnet model server https img shields io github stars awslabs mxnet model server svg style social a model server for apache mxnet from amazon web services that is able to run mxnet models as well as gluon models amazon s sagemaker runs a custom version of mms under the hood nannyml https github com nannyml nannyml https img shields io github stars nannyml nannyml svg style social an open source library to estimate post deployment model performance without access to targets capable of fully capturing the impact of data drift on performance mosec https github com mosecorg mosec https img shields io github stars mosecorg mosec svg style social a rust powered and multi stage pipelined model server which offers dynamic batching and more super easy to implement and deploy as micro services nuclio https github com nuclio nuclio https img shields io github stars nuclio nuclio svg style social a high performance serverless framework focused on data i o and compute intensive workloads it is well integrated with popular data science tools such as jupyter and kubeflow supports a variety of data and streaming sources and supports execution over cpus and gpus openscoring https github com openscoring openscoring https img shields io github stars openscoring openscoring svg style social rest web service for the true real time scoring 1 ms of scikit learn r and apache spark models pandas profiling https github com pandas profiling pandas profiling creates html profiling reports from pandas dataframe objects it extends the pandas dataframe with df profile report for quick data analysis phoenix https github com arize ai phoenix https img shields io github stars arize ai phoenix style social phoenix is an open source ml observability in a notebook to validate monitor and fine tune your generative llm cv and tabular models predictionio https github com apache predictionio https img shields io github stars apache predictionio svg style social an open source machine learning server built on top of a state of the art open source stack for developers and data scientists to create predictive engines for any machine learning task redis ai https github com redisai redisai https img shields io github stars redisai redisai svg style social a redis module for serving tensors and executing deep learning models expect changes in the api and internals seldon core https github com seldonio seldon core https img shields io github stars seldonio seldon core svg style social open source platform for deploying and monitoring machine learning models in kubernetes video https www youtube com watch v pdlapgtecby skops https github com skops dev skops https img shields io github stars skops dev skops svg style social skops is a python library helping you share your scikit learn based models and put them in production tempo https github com seldonio tempo https img shields io github stars seldonio tempo svg style social open source sdk that provides a unified interface to multiple mlops projects that enable data scientists to deploy and productionise machine learning systems tensorflow serving https github com tensorflow serving https img shields io github stars tensorflow serving svg style social high performant framework to serve tensorflow models via grpc protocol able to handle 100k requests per second per core torchserve https github com pytorch serve https img shields io github stars pytorch serve svg style social torchserve is a flexible and easy to use tool for serving pytorch models transformer deploy https github com els rd transformer deploy https img shields io github stars els rd transformer deploy svg style social transformer deploy is an efficient scalable and enterprise grade cpu gpu inference server for hugging face transformer models triton inference server https github com triton inference server server https img shields io github stars triton inference server server svg style social triton is a high performance open source serving software to deploy ai models from any framework on gpu cpu while maximizing utilization unionml https github com unionai oss unionml https img shields io github stars unionai oss unionml svg style social unionml is an open source mlops framework that aims to reduce the boilerplate and friction that comes with building models and deploying them to production vllm https github com vllm project vllm https img shields io github stars vllm project vllm svg style social vllm is a high throughput and memory efficient inference and serving engine for llms whylogs https github com whylabs whylogs python https img shields io github stars whylabs whylogs python svg style social lightweight solution for profiling and monitoring your ml data pipeline end to end adversarial robustness advbox https github com advboxes advbox https img shields io github stars advboxes advbox svg style social a toolbox to generate adversarial examples that fool neural networks in paddlepaddle pytorch caffe2 mxnet keras tensorflow and advbox can benchmark the robustness of machine learning models adversarial dnn playground https github com qdata adversarialdnn playground https img shields io github stars qdata adversarialdnn playground svg style social think tensorflow playground https playground tensorflow org but for adversarial examples a visualization tool designed for learning and teaching the attack library is limited in size but it has a nice front end to it with buttons you can press advertorch https github com borealisai advertorch https img shields io github stars borealisai advertorch svg style social library for adversarial attacks defenses specifically for pytorch artificial adversary https github com airbnb artificial adversary https img shields io github stars airbnb artificial adversary svg style social airbnb s library to generate text that reads the same to a human but passes adversarial classifiers cleverhans https github com tensorflow cleverhans https img shields io github stars tensorflow cleverhans svg style social library for testing adversarial attacks defenses maintained by some of the most important names in adversarial ml namely ian goodfellow ex google brain now apple and nicolas papernot google brain comes with some nice tutorials counterfit https github com azure counterfit https img shields io github stars azure counterfit svg style social counterfit is a command line tool and generic automation layer for assessing the security of machine learning systems deepsec https github com kleincup deepsec https img shields io github stars kleincup deepsec svg style social another systematic tool for attacking and defending deep learning models foolbox https github com bethgelab foolbox https img shields io github stars bethgelab foolbox svg style social second biggest adversarial library has an even longer list of attacks but no defenses or evaluation metrics geared more towards computer vision code easier to understand modify than art also better for exploring blackbox attacks on surrogate models adversarial robustness toolbox art https github com trusted ai adversarial robustness toolboxx https img shields io github stars trusted ai adversarial robustness toolboxx svg style social art provides tools that enable developers and researchers to defend and evaluate machine learning models and applications against the adversarial threats of evasion poisoning extraction and inference mia https github com spring epfl mia https img shields io github stars spring epfl mia svg style social a library for running membership inference attacks mia against machine learning models nicolas carlini s adversarial ml reading list https nicholas carlini com writing 2018 adversarial machine learning reading list html not a library but a curated list of the most important adversarial papers by one of the leading minds in adversarial ml nicholas carlini if you want to discover the 10 papers that matter the most i would start here robust ml https www robust ml org defenses another robustness resource maintained by some of the leading names in adversarial ml they specifically focus on defenses and ones that have published code available next to papers practical and useful textfool https github com bogdan kulynych textfool https img shields io github stars bogdan kulynych textfool svg style social plausible looking adversarial examples for text generation trickster https github com spring epfl trickster https img shields io github stars spring epfl trickster svg style social library and experiments for attacking machine learning in discrete domains using graph search automl autogluon https github com awslabs autogluon https img shields io github stars awslabs autogluon svg style social automated feature model and hyperparameter selection for tabular image and text data on top of popular machine learning libraries scikit learn lightgbm catboost pytorch mxnet autokeras https github com jhfjhfj1 autokeras https img shields io github stars jhfjhfj1 autokeras svg style social automl library for keras based on auto keras efficient neural architecture search with network morphism https arxiv org abs 1806 10282 automl gs https github com minimaxir automl gs https img shields io github stars blue yonder tsfresh svg style social automatic feature and model search with code generation in python on top of common data science libraries tensorflow sklearn etc auto sklearn https github com automl auto sklearn https img shields io github stars automl auto sklearn svg style social framework to automate algorithm and hyperparameter tuning for sklearn colombus http i stanford edu hazy victor columbus a scalable framework to perform exploratory feature selection implemented in r enas via parameter sharing https github com melodyguan enas efficient neural architecture search via parameter sharing by authors of paper https arxiv org abs 1802 03268 enas pytorch https github com carpedm20 enas pytorch https img shields io github stars carpedm20 enas pytorch svg style social efficient neural architecture search enas in pytorch based on this paper https arxiv org abs 1802 03268 enas tensorflow https github com mingukkang enas tensorflow https img shields io github stars mingukkang enas tensorflow svg style social efficient neural architecture search via parameter sharing enas micro search tensorflow code for windows user feature engine https github com feature engine feature engine https img shields io github stars feature engine feature engine svg style social feature engine is a python library that contains several transformers to engineer features for use in machine learning models featuretools https github com alteryx featuretools https img shields io github stars alteryx featuretools svg style social an open source framework for automated feature engineering flaml https github com microsoft flaml https img shields io github stars microsoft flaml svg style social flaml is a fast library for automated machine learning tuning go featureprocessing https github com nikolaydubina go featureprocessing https img shields io github stars nikolaydubina go featureprocessing svg style social a feature pre processing framework in go that matches functionality of sklearn katib https github com kubeflow katib https img shields io github stars kubeflow katib svg style social a kubernetes based system for hyperparameter tuning and neural architecture search keras tuner https github com keras team keras tuner https img shields io github stars keras team keras tuner style social keras tuner is an easy to use distributable hyperparameter optimization framework that solves the pain points of performing a hyperparameter search keras tuner makes it easy to define a search space and leverage included algorithms to find the best hyperparameter values maggy https github com logicalclocks maggy https img shields io github stars logicalclocks maggy svg style social asynchronous directed hyperparameter search and parallel ablation studies on apache spark video https www youtube com watch v 0hd1iyel03w neural architecture search with controller rnn https github com titu1994 neural architecture search https img shields io github stars titu1994 neural architecture search svg style social basic implementation of controller rnn from neural architecture search with reinforcement learning https arxiv org abs 1611 01578 and learning transferable architectures for scalable image recognition https arxiv org abs 1707 07012 neural network intelligence https github com microsoft nni https img shields io github stars microsoft nni svg style social nni neural network intelligence is a toolkit to help users run automated machine learning automl experiments optuna https github com optuna optuna https img shields io github stars optuna optuna svg style social optuna is an automatic hyperparameter optimization software framework particularly designed for machine learning oss vizier https github com google vizier https img shields io github stars google vizier svg style social oss vizier is a python based service for black box optimization and research one of the first hyperparameter tuning services designed to work at scale sklearn deap https github com rsteca sklearn deap https img shields io github stars rsteca sklearn deap svg style social use evolutionary algorithms instead of gridsearch in scikit learn tpot https github com epistasislab tpot https img shields io github stars epistasislab tpot svg style social automation of sklearn pipeline creation including feature selection pre processor etc tsfresh https github com blue yonder tsfresh https img shields io github stars blue yonder tsfresh svg style social automatic extraction of relevant features from time series upgini https github com upgini upgini https img shields io github stars upgini upgini svg style social free automated data feature enrichment library for machine learning automatically searches through thousands of ready to use features from public and community shared data sources and enriches your training dataset with only the accuracy improving features data pipeline apache airflow https github com apache airflow https img shields io github stars apache airflow svg style social data pipeline framework built in python including scheduler dag definition and a ui for visualisation apache nifi https github com apache nifi https img shields io github stars apache nifi svg style social apache nifi was made for dataflow it supports highly configurable directed graphs of data routing transformation and system mediation logic argo workflows https github com argoproj argo workflows https img shields io github stars argoproj argo workflows svg style social argo workflows is an open source container native workflow engine for orchestrating parallel jobs on kubernetes argo workflows is implemented as a kubernetes crd custom resource definition azkaban https github com azkaban azkaban https img shields io github stars azkaban azkaban svg style social azkaban is a batch workflow job scheduler created at linkedin to run hadoop jobs azkaban resolves the ordering through job dependencies and provides an easy to use web user interface to maintain and track your workflows basin https github com basin etl basin https img shields io github stars basin etl basin svg style social visual programming editor for building spark and pyspark pipelines batchflow https github com analysiscenter batchflow https img shields io github stars analysiscenter batchflow svg style social batchflow helps data scientists conveniently work with random or sequential batches of your data and define data processing and machine learning workflows for large datasets bonobo https github com python bonobo bonobo https img shields io github stars python bonobo bonobo svg style social etl framework for python 3 5 with focus on simple atomic operations working concurrently on rows of data chronos https github com mesos chronos https img shields io github stars mesos chronos svg style social more of a job scheduler for mesos than etl pipeline couler https github com couler proj couler https img shields io github stars couler proj couler svg style social unified interface for constructing and managing machine learning workflows on different workflow engines such as argo workflows tekton pipelines and apache airflow d6tflow https github com d6t d6tflow https img shields io github stars d6t d6tflow svg style social a python library that allows for building complex data science workflows on python dall e flow https github com jina ai dalle flow https img shields io github stars jina ai dalle flow svg style social dall e flow is an interactive workflow for generating high definition images from text prompt dagster https github com dagster io dagster https img shields io github stars dagster io dagster svg style social a data orchestrator for machine learning analytics and etl dbnd https github com databand ai dbnd https img shields io github stars databand ai dbnd svg style social dbnd is an agile pipeline framework that helps data engineering teams track and orchestrate their data processes dbt https github com dbt labs dbt core https img shields io github stars dbt labs dbt core svg style social etl tool for running transformations inside data warehouses flyte https github com flyteorg flyte https img shields io github stars lyft flyte svg style social lyft s cloud native machine learning and data processing platform demo https youtu be kdujgsp1h9u t 1451 genie https github com netflix genie https img shields io github stars netflix genie svg style social job orchestration engine to interface and trigger the execution of jobs from hadoop based systems gokart https github com m3dev gokart https img shields io github stars m3dev gokart svg style social wrapper of the data pipeline luigi kedro https github com quantumblacklabs kedro https img shields io github stars quantumblacklabs kedro svg style social kedro is a workflow development tool that helps you build data pipelines that are robust scalable deployable reproducible and versioned visualization of the kedro workflows can be done by kedro viz https github com quantumblacklabs kedro viz ludwig https github com ludwig ai ludwig https img shields io github stars ludwig ai ludwig svg style social ludwig is a declarative machine learning framework that makes it easy to define machine learning pipelines using a simple and flexible data driven configuration system luigi https github com spotify luigi https img shields io github stars spotify luigi svg style social luigi is a python module that helps you build complex pipelines of batch jobs handling dependency resolution workflow management visualisation etc metaflow https github com netflix metaflow https img shields io github stars netflix metaflow svg style social a framework for data scientists to easily build and manage real life data science projects neuraxle https github com neuraxio neuraxle https img shields io github stars neuraxio neuraxle svg style social a framework for building neat pipelines providing the right abstractions to chain your data transformation and prediction steps with data streaming as well as doing hyperparameter searches automl oozie https github com apache oozie https img shields io github stars apache oozie svg style social workflow scheduler for hadoop jobs pachyderm https github com pachyderm pachyderm https img shields io github stars pachyderm pachyderm svg style social open source distributed processing framework build on kubernetes focused mainly on dynamic building of production machine learning pipelines video https www youtube com watch v lamkvhe2rsm pipelinex https github com minyus pipelinex https img shields io github stars minyus pipelinex svg style social based on kedro and mlflow full comparison is found here https github com minyus python packages for pipeline workflow ploomber https github com ploomber ploomber https img shields io github stars ploomber ploomber svg style social the fastest way to build data pipelines develop iteratively deploy anywhere prefect core https github com prefecthq prefect https img shields io github stars prefecthq prefect svg style social workflow management system that makes it easy to take your data pipelines and add semantics like retries logging dynamic mapping caching failure notifications and more setl https github com setl developers setl https img shields io github stars setl developers setl svg style social a simple spark powered etl framework that helps you structure your etl projects modularize your data transformation logic and speed up your development snakemake https github com snakemake snakemake https img shields io github stars snakemake snakemake svg style social workflow management system for reproducible and scalable data analyses towhee https github com towhee io towhee https img shields io github stars towhee io towhee svg style social general purpose machine learning pipeline for generating embedding vectors using one or many ml models data labelling argilla https github com argilla io argilla https img shields io github stars argilla io argilla svg style social argilla helps domain experts and data teams to build better nlp datasets in less time baal https github com baal org baal https img shields io github stars baal org baal svg style social baal is an active learning library that supports both industrial applications and research usecases brat rapid annotation tool https github com nlplab brat https img shields io github stars nlplab brat svg style social web based text annotation tool for named entity recogntion task cleanlab https github com cleanlab cleanlab https img shields io github stars cleanlab cleanlab style social python library for data centric ai can automatically find mislabeled data detect outliers estimate consensus annotator quality for multi annotator datasets suggest which data is best to re label next coco annotator https github com jsbroks coco annotator https img shields io github stars jsbroks coco annotator svg style social web based image segmentation tool for object detection localization and keypoints computer vision annotation tool cvat https github com opencv cvat https img shields io github stars opencv cvat svg style social opencv s web based annotation tool for both videos and images for computer algorithms doccano https github com chakki works doccano https img shields io github stars chakki works doccano svg style social open source text annotation tools for humans providing functionality for sentiment analysis named entity recognition and machine translation imagetagger https github com bit bots imagetagger https img shields io github stars bit bots imagetagger svg style social image labelling tool with support for collaboration supporting bounding box polygon line point labelling label export etc imglab https github com naturalintelligence imglab https img shields io github stars naturalintelligence imglab svg style social image annotation tool for bounding boxes with auto suggestion and extensibility for plugins label studio https github com heartexlabs label studio https img shields io github stars heartexlabs label studio svg style social multi domain data labeling and annotation tool with standardized output format labelimg https github com tzutalin labelimg https img shields io github stars tzutalin labelimg svg style social open source graphical image annotation tool writen in python using qt for graphical interface focusing primarily on bounding boxes makesense ai https github com skalskip make sense https img shields io github stars skalskip make sense svg style social free to use online tool for labelling photos prepared labels can be downloaded in one of multiple supported formats medtagger https github com medtagger medtagger https img shields io github stars medtagger medtagger svg style social a collaborative framework for annotating medical datasets using crowdsourcing modal https github com modal python modal https img shields io github stars modal python modal svg style social modal is an active learning framework designed with modularity flexibility and extensibility in mind openlabeling https github com cartucho openlabeling https img shields io github stars cartucho openlabeling svg style social open source tool for labelling images with support for labels edges as well as image resizing and zooming in pixelannotationtool https github com abreheret pixelannotationtool https img shields io github stars abreheret pixelannotationtool svg style social image annotation tool with ability to colour on the images to select labels for segmentation process is semi automated with the watershed marked algorithm of opencv docs opencv org 3 1 0 d7 d1b group imgproc misc html ga3267243e4d3f95165d55a618c65ac6e1 refinery https github com code kern ai refinery https img shields io github stars code kern ai refinery svg style social the data scientist s open source choice to scale assess and maintain natural language data rubrix https github com recognai rubrix https img shields io github stars recognai rubrix svg style social open source tool for tracking exploring and labeling data for ai projects semantic segmentation editor https github com hitachi automotive and industry lab semantic segmentation editor https img shields io github stars hitachi automotive and industry lab semantic segmentation editor svg style social hitachi s open source tool for labelling camera and lidar data snorkel https github com snorkel team snorkel https img shields io github stars snorkel team snorkel svg style social snorkel is a system for quickly generating training data with weak supervision superintendent https github com janfreyberg superintendent https img shields io github stars janfreyberg superintendent svg style social superintendent provides an ipywidget based interactive labelling tool for your data vgg image annotator via http www robots ox ac uk vgg software via a simple and standalone manual annotation software for image audio and video via runs in a web browser and does not require any installation or setup metadata management amundsen https github com amundsen io amundsen https img shields io github stars amundsen io amundsen svg style social amundsen is a metadata driven application for improving the productivity of data analysts data scientists and engineers when interacting with data arangoml pipeline https github com arangoml arangopipe https img shields io github stars arangoml arangopipe svg style social arangoml pipeline is a common and extensible metadata layer for machine learning pipelines which allows data scientists and dataops to manage all information related to their ml pipeline in one place apache atlas https github com apache atlas https img shields io github stars apache atlas svg style social apache atlas framework is an extensible set of core foundational governance services enabling enterprises to effectively and efficiently meet their compliance requirements within hadoop and allows integration with the whole enterprise data ecosystem datahub https github com linkedin datahub https img shields io github stars linkedin datahub svg style social datahub is linkedin s generalized metadata search discovery tool marquez https github com marquezproject marquez https img shields io github stars marquezproject marquez svg style social marquez is an open source metadata service for the collection aggregation and visualization of a data ecosystem s metadata metacat https github com netflix metacat https img shields io github stars netflix metacat svg style social metacat is a unified metadata exploration api service metacat focusses on solving these problems 1 federated views of metadata systems 2 arbitrary metadata storage about data sets 3 metadata discovery ml metadata https github com google ml metadata https img shields io github stars google ml metadata svg style social a library for recording and retrieving metadata associated with ml developer and data scientist workflows model card toolkit https github com tensorflow model card toolkit https img shields io github stars tensorflow model card toolkit svg style social streamlines and automates generation of model cards https modelcards withgoogle com about data storage optimisation aistore https github com nvidia aistore https img shields io github stars nvidia aistore svg style social aistore is a lightweight object storage system with the capability to linearly scale out with each added storage node and a special focus on petascale deep learning alluxio https github com alluxio alluxio https img shields io github stars alluxio alluxio svg style social a virtual distributed storage system that bridges the gab between computation frameworks and storage systems apache arrow https github com apache arrow https img shields io github stars apache arrow svg style social in memory columnar representation of data compatible with pandas hadoop based systems etc apache druid https github com apache druid https img shields io github stars apache druid svg style social a high performance real time analytics database check this article https towardsdatascience com introduction to druid 4bf285b92b5a for introduction apache ignite https github com apache ignite https img shields io github stars apache ignite svg style social a memory centric distributed database caching and processing platform for transactional analytical and streaming workloads delivering in memory speeds at petabyte scale demo https www youtube com watch v xt4pwq ypw apache parquet https github com apache parquet mr https img shields io github stars apache parquet mr svg style social on disk columnar representation of data compatible with pandas hadoop based systems etc apache pinot https github com apache incubator pinot https img shields io github stars apache incubator pinot svg style social a realtime distributed olap datastore comparison of the open source olap systems for big data clickhouse druid and pinot is found here https medium com leventov comparison of the open source olap systems for big data clickhouse druid and pinot 8e042a5ed1c7 bayesdb https github com probcomp bayeslite https img shields io github stars probcomp bayeslite svg style social a bayesian database table for querying the probable implications of data as easily as sql databases query the data itself video https www youtube com watch v 2ws84s6id1o chroma https github com chroma core chroma https img shields io github stars chroma core chroma svg style social bayesdb is an ai native embedding database clickhouse https github com clickhouse clickhouse https img shields io github stars clickhouse clickhouse svg style social clickhouse is an open source column oriented database management system delta lake https github com delta io delta https img shields io github stars delta io delta svg style social delta lake is a storage layer that brings scalable acid transactions to apache spark and other big data engines edgedb https github com edgedb edgedb https img shields io github stars edgedb edgedb svg style social nosql interface for postgres that allows for object interaction to data stored gptcache https github com zilliztech gptcache https img shields io github stars zilliztech gptcache svg style social gptcache is a library for creating semantic cache for large language model queries hopsfs https github com hopshadoop hops https img shields io github stars hopshadoop hops svg style social hdfs compatible file system with scale out strongly consistent metadata influxdb https github com influxdata influxdb https img shields io github stars influxdata influxdb svg style social scalable datastore for metrics events and real time analytics milvus https github com milvus io milvus https img shields io github stars milvus io milvus svg style social milvus is a cloud native open source vector database built to manage embedding vectors generated by machine learning models and neural networks pgvector https github com pgvector pgvector https img shields io github stars pgvector pgvector svg style social pgvector helps with vector similarity search for postgres timescaledb https github com timescale timescaledb https img shields io github stars timescale timescaledb svg style social an open source time series sql database optimized for fast ingest and complex queries packaged as a postgresql extension video www youtube com watch v zbjub8bqpye weaviate https github com semi technologies weaviate https img shields io github stars semi technologies weaviate svg style social a low latency vector search engine graphql restful with out of the box support for different media types modules include semantic search q a classification customizable models pytorch tensorflow keras and more zarr https github com zarr developers zarr python https img shields io github stars zarr developers zarr python svg style social python implementation of chunked compressed n dimensional arrays designed for use in parallel computing computation load distribution analytics zoo https github com intel analytics analytics zoo https img shields io github stars intel analytics analytics zoo svg style social a unified data analytics and ai platform for distributed tensorflow keras and pytorch on apache spark flink ray apache spark mllib https spark apache org mllib apache spark s scalable machine learning library in java scala python and r bagua https github com baguasys bagua https img shields io github stars baguasys bagua svg style social bagua is a performant and flexible distributed training framework for pytorch providing a faster alternative to pytorch ddp and horovod it supports advanced distributed training algorithms such as quantization and decentralization beam https github com apache beam https img shields io github stars apache beam svg style social apache beam is a unified programming model for batch and streaming bigdl https github com intel analytics bigdl https img shields io github stars intel analytics bigdl svg style social deep learning framework on top of spark hadoop to distribute data and computations across a hdfs system colossal ai https github com hpcaitech colossalai https img shields io github stars hpcaitech colossalai svg style social a unified deep learning system for big model era which helps users to efficiently and quickly deploy large ai model training and inference dask https github com dask dask https img shields io github stars dask dask svg style social distributed parallel processing framework for pandas and numpy computations video https www youtube com watch v ra 2qdipvng deap https github com deap deap https img shields io github stars deap deap svg style social a novel evolutionary computation framework for rapid prototyping and testing of ideas it seeks to make algorithms explicit and data structures transparent it works in perfect harmony with parallelisation mechanisms such as multiprocessing and scoop deepspeed https github com microsoft deepspeed https img shields io github stars microsoft deepspeed svg style social a deep learning optimization library lightweight pytorch wrapper that makes distributed training easy efficient and effective fiber https github com uber fiber https img shields io github stars uber fiber svg style social distributed computing library for modern computer clusters from uber flashlight https github com flashlight flashlight https img shields io github stars flashlight flashlight svg style social a fast flexible machine learning library written entirely in c from the facebook ai research and the creators of torch tensorflow eigen and deep speech hivemind https github com learning at home hivemind https img shields io github stars learning at home hivemind svg style social decentralized deep learning in pytorch horovod https github com uber horovod https img shields io github stars uber horovod svg style social uber s distributed training framework for tensorflow keras and pytorch lightgbm https github com microsoft lightgbm https img shields io github stars microsoft lightgbm svg style social lightgbm is a gradient boosting framework that uses tree based learning algorithms numpywren https github com vaishaal numpywren https img shields io github stars vaishaal numpywren svg style social scientific computing framework build on top of pywren to enable numpy like distributed computations pywren https github com pywren pywren https img shields io github stars pywren pywren svg style social answer the question of the cloud button for python function execution it s a framework that abstracts aws lambda to enable data scientists to execute any python function video https www youtube com watch v oskqytbbdju pytorch lightning https github com pytorchlightning pytorch lightning https img shields io github stars pytorchlightning pytorch lightning svg style social lightweight pytorch research framework that allows you to easily scale your models to gpus and tpus and use all the latest best practices without the engineering boilerplate video https www youtube com watch v qhww1jh7idu t 678s ray https github com ray project ray https img shields io github stars ray project ray svg style social ray is a flexible high performance distributed execution framework for machine learning video https www youtube com watch v d oz7e4v u0 tensorflowonspark https github com yahoo tensorflowonspark https img shields io github stars yahoo tensorflowonspark svg style social tensorflowonspark brings tensorflow programs to apache spark clusters vespa https github com vespa engine vespa https img shields io github stars vespa engine vespa svg style social vespa is an engine for low latency computation over large data sets model serialisation java pmml api https github com jpmml java libraries for consuming and producing pmml files containing models from different frameworks including pyspark2pmml https github com jpmml pyspark2pmml https img shields io github stars jpmml pyspark2pmml svg style social r2pmml https github com jpmml r2pmml https img shields io github stars jpmml r2pmml svg style social sklearn2pmml https github com jpmml jpmml sklearn https img shields io github stars jpmml jpmml sklearn svg style social sparklyr2pmml https github com jpmml sparklyr2pmml https img shields io github stars jpmml sparklyr2pmml svg style social mmdnn https github com microsoft mmdnn https img shields io github stars microsoft mmdnn svg style social cross framework solution to convert visualize and diagnose deep neural network models neural network exchange format nnef https www khronos org nnef a standard format to store models across torch caffe tensorflow theano chainer caffe2 pytorch and mxnet onnx https github com onnx onnx https img shields io github stars onnx onnx svg style social open neural network exchange format pfa https dmg org pfa created by the same organisation as pmml the predicted format for analytics is an emerging standard for statistical models and data transformation engines pmml https dmg org pmml the predictive model markup language standard in xml video https www youtube com watch v 5pzm2pz8q8 tensorstore https github com google tensorstore https img shields io github stars google tensorstore svg style social tensorstore is an open source c and python software library designed for storage and manipulation of large multi dimensional arrays optimized computation bindsnet https github com bindsnet bindsnet https img shields io github stars bindsnet bindsnet svg style social bindsnet is a spiking neural network simulation library geared towards the development of biologically inspired algorithms for machine learning braincog https github com braincog x brain cog https img shields io github stars braincog x brain cog svg style social braincog brain inspired cognitive intelligence engine is a brain inspired spiking neural network based platform for brain inspired artificial intelligence and simulating brains at multiple scales composer https github com mosaicml composer https img shields io github stars mosaicml composer svg style social composer is a pytorch library that enables you to train neural networks faster at lower cost and to higher accuracy cudf https github com rapidsai cudf https img shields io github stars rapidsai cudf svg style social built based on the apache arrow columnar memory format cudf is a gpu dataframe library for loading joining aggregating filtering and otherwise manipulating data cuml https github com rapidsai cuml https img shields io github stars rapidsai cuml svg style social cuml is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible apis with other rapids projects cupy https github com cupy cupy https img shields io github stars cupy cupy svg style social an implementation of numpy compatible multi dimensional array on cuda cupy consists of the core multi dimensional array class cupy ndarray and many functions on it deepspeed mii https github com microsoft deepspeed mii https img shields io github stars microsoft deepspeed mii svg style social deepspeed mii makes low latency and high throughput inference possible powered by deepspeed flax https github com google flax https img shields io github stars google flax svg style social a neural network library and ecosystem for jax designed for flexibility ggml https github com ggerganov ggml https img shields io github stars ggerganov ggml svg style social a tensor library for machine learning that you can efficiently run gpt 2 and gpt j inference on the cpu h2o 3 https github com h2oai h2o 3 https img shields io github stars h2oai h2o 3 svg style social fast scalable machine learning platform for smarter applications deep learning gradient boosting xgboost random forest generalized linear modeling logistic regression elastic net k means pca stacked ensembles automatic machine learning automl etc jax https github com google jax https img shields io github stars google jax svg style social composable transformations of python numpy programs differentiate vectorize jit to gpu tpu and more modin https github com modin project modin https img shields io github stars modin project modin svg style social speed up your pandas workflows by changing a single line of code nebullvm https github com nebuly ai nebullvm https img shields io github stars nebuly ai nebullvm svg style social nebullvm is an ecosystem of plug and play modules to boost the performances of your ai systems the optimization modules are stack agnostic and work with any library they are designed to be easily integrated into your system providing a quick and seamless boost to its performance nevergrad https github com facebookresearch nevergrad https img shields io github stars facebookresearch nevergrad svg style social nevergrad is a gradient free optimization platform norse https github com norse norse https img shields io github stars norse norse svg style social norse aims to exploit the advantages of bio inspired neural components which are sparse and event driven a fundamental difference from artificial neural networks numba https github com numba numba https img shields io github stars numba numba svg style social a compiler for python array and numerical functions numpygroupies https github com ml31415 numpy groupies https img shields io github stars ml31415 numpy groupies svg style social optimised tools for group indexing operations aggregated sum and more openflamingo https github com mlfoundations open flamingo https img shields io github stars mlfoundations open flamingo tensorflow svg style social openflamingo is an open source framework for training large multimodal models openvino https github com openvinotoolkit openvino https img shields io github stars openvinotoolkit openvino tensorflow svg style social openvino is an open source toolkit for optimizing and deploying ai inference peft https github com huggingface peft https img shields io github stars huggingface peft svg style social parameter efficient fine tuning peft methods enable efficient adaptation of pre trained language models plms to various downstream applications without fine tuning all the model s parameters snntorch https github com jeshraghian snntorch https img shields io github stars jeshraghian snntorch svg style social snntorch is a deep and online learning library with spiking neural networks in python tensor2tensor https github com tensorflow tensor2tensor https img shields io github stars tensorflow tensor2tensor svg style social tensor2tensor is a library of deep learning models and datasets designed to make deep learning more accessible and accelerate ml research torchopt https github com metaopt torchopt https img shields io github stars metaopt torchopt svg style social torchopt is an efficient library for differentiable optimization built upon pytorch vaex https github com vaexio vaex https img shields io github stars vaexio vaex svg style social vaex is a high performance python library for lazy out of core dataframes similar to pandas to visualize and explore big tabular datasets vaex uses memory mapping zero memory copy policy and lazy computations for best performance no memory wasted vowpal wabbit https github com vowpalwabbit vowpal wabbit https img shields io github stars vowpalwabbit vowpal wabbit svg style social vowpal wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online hashing allreduce reductions learning2search active and interactive learning vulkan kompute https github com axsaucedo vulkan kompute https img shields io github stars axsaucedo vulkan kompute svg style social blazing fast lightweight and mobile phone enabled vulkan compute framework optimized for advanced gpu data processing usecases weld https github com weld project weld https img shields io github stars weld project weld svg style social high performance runtime for data analytics applications here is an interview https www notamonadtutorial com weld accelerating numpy scikit and pandas as much as 100x with rust and llvm with weld s main contributor xgboost https github com dmlc xgboost https img shields io github stars dmlc xgboost svg style social xgboost is an optimized distributed gradient boosting library designed to be highly efficient flexible and portable data stream processing apache flink https github com apache flink https img shields io github stars apache flink svg style social open source stream processing framework with powerful stream and batch processing capabilities apache samza https github com apache samza https img shields io github stars apache samza svg style social distributed stream processing framework it uses apache kafka for messaging and apache hadoop yarn to provide fault tolerance processor isolation security and resource management brooklin https github com linkedin brooklin https img shields io github stars linkedin brooklin svg style social distributed stream processing framework it uses apache kafka for messaging and apache hadoop yarn to provide fault tolerance processor isolation security and resource management faust https github com robinhood faust https img shields io github stars robinhood faust svg style social streaming library built on top of python s asyncio library using the async kafka client inspired by the kafka streaming library apache spark https spark apache org streaming https img shields io github stars apache spark svg style social micro batch processing for streams using the apache spark framework as a backend supporting stateful exactly once semantics apache kafka https github com apache kafka https img shields io github stars apache kafka svg style social kafka client library for buliding applications and microservices where the input and output are stored in kafka clusters outlier and anomaly detection adtk https github com arundo adtk https img shields io github stars arundo adtk svg style social a python toolkit for rule based unsupervised anomaly detection in time series alibi detect https github com seldonio alibi detect https img shields io github stars seldonio alibi detect svg style social alibi detect is a python package focused on outlier adversarial and concept drift detection dboost https github com cpitclaudel dboost https img shields io github stars cpitclaudel dboost svg style social outlier detection in heterogeneous datasets using automatic tuple expansion check this paper https core ac uk download pdf 78067844 pdf for further details deequ https github com awslabs deequ https img shields io github stars awslabs deequ svg style social a library built on top of apache spark for defining unit tests for data which measure data quality in large datasets deep anomaly detection with outlier exposure https github com hendrycks outlier exposure https img shields io github stars hendrycks outlier exposure svg style social outlier exposure oe is a method for improving anomaly detection performance in deep learning models paper https arxiv org pdf 1812 04606 pdf pyod https github com yzhao062 pyod https img shields io github stars yzhao062 pyod svg style social a python toolbox for scalable outlier detection anomaly detection suod scalable unsupervised outlier detection https github com yzhao062 suod https img shields io github stars yzhao062 suod svg style social an acceleration system for large scale anomaly outlier detection tensorflow data validation tfdv https github com tensorflow data validation https img shields io github stars tensorflow data validation svg style social library for exploring and validating machine learning data tods https github com datamllab tods https img shields io github stars datamllab tods svg style social tods is a full stack automated machine learning system for outlier detection on multivariate time series data feature store butterfree https github com quintoandar butterfree https img shields io github stars quintoandar butterfree svg style social a tool for building feature stores which allows you to transform your raw data into beautiful features feast https github com feast dev feast https img shields io github stars feast dev feast svg style social feast feature store is an open source feature store for machine learning feast is the fastest path to manage existing infrastructure to productionize analytic data for model training and online inference featureform https github com featureform featureform https img shields io github stars featureform featureform svg style social a virtual featurestore plug play with your existing infra data scientist approved discovery governance lineage collaboration just a pip install away supports pandas python spark sql integrations with major cloud vendors hopsworks feature store https github com logicalclocks hopsworks https img shields io github stars logicalclocks hopsworks svg style social offline online feature store for ml video https www youtube com watch v n1bjpk1smdg ivory https github com antony a1 ivory https img shields io github stars antony a1 ivory svg style social ivory defines a specification for how to store feature data and provides a set of tools for querying it it does not provide any tooling for producing feature data in the first place all ivory commands run as mapreduce jobs so it assumed that feature data is maintained on hdfs veri https github com bgokden veri https img shields io github stars bgokden veri svg style social veri is a feature label store feature label store allows storing features as keys and labels as values querying values is only possible with knn using features veri also supports creating sub sample spaces of data by default data science notebook apache zeppelin https github com apache zeppelin https img shields io github stars apache zeppelin svg style social web based notebook that enables data driven interactive data analytics and collaborative documents with sql scala and more binder https github com jupyterhub binder ttps img shields io github stars jupyterhub binder svg style social binder hosts notebooks in an executable environment for free h2o flow https github com h2oai h2o flow jupyter notebook like interface for h2o to create save and re use flows jupyter notebooks https github com jupyter notebook https img shields io github stars jupyter notebook svg style social web interface python sandbox environments for reproducible development ml workspace https github com ml tooling ml workspace https img shields io github stars ml tooling ml workspace svg style social all in one web ide for machine learning and data science combines jupyter vs code tensorflow and many other tools libraries into one docker image net interactive https github com dotnet interactive https img shields io github stars dotnet interactive svg style social net interactive takes the power of net and embeds it into your interactive experiences papermill https github com nteract papermill https img shields io github stars nteract papermill svg style social papermill is a library for parameterizing notebooks and executing them like python scripts polynote https github com polynote polynote https img shields io github stars stencila stencila svg style social polynote is an experimental polyglot notebook environment currently it supports scala and python with or without spark sql and vega rmarkdown https github com rstudio rmarkdown https img shields io github stars rstudio rmarkdown svg style social the rmarkdown package is a next generation implementation of r markdown based on pandoc stencila https github com stencila stencila https img shields io github stars stencila stencila svg style social stencila is a platform for creating collaborating on and sharing data driven content content that is transparent and reproducible voil https github com voila dashboards voila https img shields io github stars voila dashboards voila svg style social voil turns jupyter notebooks into standalone web applications that can e g be used as dashboards neural search annoy https github com spotify annoy https img shields io github stars spotify annoy svg style social annoy approximate nearest neighbors oh yeah is a c library with python bindings to search for points in space that are close to a given query point clip as service https github com jina ai clip as service https img shields io github stars jina ai clip as service svg style social clip as service is a low latency high scalability service for embedding images and text it can be easily integrated as a microservice into neural search solutions docarray https github com docarray docarray https img shields io github stars docarray docarray svg style social docarray is a library for nested unstructured multimodal data in transit including text image audio video 3d mesh etc it allows deep learning engineers to efficiently process embed search recommend store and transfer multimodal data with a pythonic api faiss https github com facebookresearch faiss https img shields io github stars facebookresearch faiss svg style social faiss is a library for efficient similarity search and clustering of dense vectors finetuner https github com jina ai finetuner https img shields io github stars jina ai finetuner svg style social finetuner provides an effective way to improve performance on neural search tasks ngt https github com yahoojapan ngt https img shields io github stars yahoojapan ngt svg style social ngt provides commands and a library for performing high speed approximate nearest neighbor searches against a large volume of data in high dimensional vector data space nmslib https github com nmslib nmslib https img shields io github stars nmslib nmslib svg style social non metric space library nmslib an efficient similarity search library and a toolkit for evaluation of k nn methods for generic non metric spaces qdrant https github com qdrant qdrant https img shields io github stars qdrant qdrant svg style social an open source vector similarity search engine with extended filtering support industry strength cv deep lake https github com activeloopai deeplake https img shields io github stars activeloopai deeplake svg style social deep lake is a data infrastructure optimized for computer vision igibson https github com stanfordvl igibson https img shields io github stars stanfordvl igibson svg style social igibson is a simulation environment providing fast visual rendering and physics simulation based on bullet kerascv https github com keras team keras cv https img shields io github stars keras team keras cv svg style social kerascv is a library of modular computer vision oriented keras components supergradients https github com deci ai super gradients https img shields io github stars deci ai super gradients svg style social supergradients is an open source library for training pytorch based computer vision models industry strength nlp adaptnlp https github com novetta adaptnlp https img shields io github stars novetta adaptnlp svg style social built atop zalando research s flair and hugging face s transformers library adaptnlp provides machine learning researchers and scientists a modular and adaptive approach to a variety of nlp tasks with an easy api for training inference and deploying nlp based microservices blackstone https github com iclrandd blackstone https img shields io github stars iclrandd blackstone svg style social blackstone is a spacy model and library for processing long form unstructured legal text blackstone is an experimental research project from the incorporated council of law reporting for england and wales research lab iclr d coqui stt https github com coqui ai stt https img shields io github stars coqui ai stt svg style social coqui stt is a fast open source multi platform deep learning toolkit for training and deploying speech to text models ctrl https github com salesforce ctrl https img shields io github stars salesforce ctrl svg style social a conditional transformer language model for controllable generation released by salesforce dspy https github com stanfordnlp dspy https img shields io github stars stanfordnlp dspy svg style social a framework for programming with foundation models dust https github com dust tt dust https img shields io github stars dust tt dust svg style social dust assists in the design and deployment of large language model apps espnet https github com espnet espnet https img shields io github stars espnet espnet svg style social espnet is an end to end speech processing toolkit facebook s xlm https github com facebookresearch xlm https img shields io github stars facebookresearch xlm svg style social pytorch original implementation of cross lingual language model pretraining which includes bert xlm nmt xnli pkm etc fastchat https github com lm sys fastchat https img shields io github stars lm sys fastchat svg style social fastchat is an open platform for training serving and evaluating large language model based chatbots flair https github com zalandoresearch flair https img shields io github stars zalandoresearch flair svg style social simple framework for state of the art nlp developed by zalando which builds directly on pytorch flexgen https github com fminference flexgen https img shields io github stars fminference flexgen svg style social flexgen is a high throughput generation engine for running large language models with limited gpu memory gluonnlp https github com dmlc gluon nlp https img shields io github stars dmlc gluon nlp svg style social gluonnlp is a toolkit that enables easy text preprocessing datasets loading and neural models building to help you speed up your natural language processing nlp research gretel synthetics https github com gretelai gretel synthetics https img shields io github stars gretelai gretel synthetics svg style social gretel synthetics is a synthetic data generators for structured and unstructured text featuring differentially private learning grover https github com rowanz grover https img shields io github stars rowanz grover svg style social grover is a model for neural fake news both generation and detection however it probably can also be used for other generation tasks guardrails https github com shreyar guardrails https img shields io github stars shreyar guardrails svg style social guardrails is a package that lets a user add structure type and quality guarantees to the outputs of large language models h2ogpt https github com h2oai h2ogpt https img shields io github stars h2oai h2ogpt svg style social h2ogpt is an open source generative ai gives organizations like yours the power to own large language models while preserving your data ownership haystack https github com deepset ai haystack https img shields io github stars deepset ai haystack svg style social haystack is an open source nlp framework to interact with your data using transformer models and llms gpt 3 and alike haystack offers production ready tools to quickly build chatgpt like question answering semantic search text generation and more interactive composition explorer https github com oughtinc ice https img shields io github stars oughtinc ice svg style social ice is a python library and trace visualizer for language model programs kashgari https github com brikerman kashgari https img shields io github stars brikerman kashgari svg style social kashgari is a simple and powerful nlp transfer learning framework build a state of art model in 5 minutes for named entity recognition ner part of speech tagging pos and text classification tasks lamini https github com lamini ai lamini https img shields io github stars lamini ai lamini svg style social lamini is an llm engine for rapidly customizing models langchain https github com hwchase17 langchain https img shields io github stars hwchase17 langchain svg style social langchain assists in building applications with llms through composability llamaindex https github com jerryjliu llama index https img shields io github stars jerryjliu llama index svg style social llamaindex gpt index is a data framework for your llm application llama https github com facebookresearch llama https img shields io github stars ggerganov llama cpp svg style social llama is intended as a minimal hackable and readable example to load llama arxiv models and run inference lmflow https github com optimalscale lmflow https img shields io github stars optimalscale lmflow svg style social lmflow is an extensible convenient and efficient toolbox for finetuning large machine learning models megatron lm https github com nvidia megatron lm https img shields io github stars nvidia megatron lm svg style social megatron lm is a highly optimized and efficient library for training large language models mlc llm https github com mlc ai mlc llm https img shields io github stars mlc ai mlc llm svg style social mlc llm is a universal solution that allows any language models to be deployed natively on a diverse set of hardware backends and native applications plus a productive framework for everyone to further optimize model performance for their own use cases ollama https github com jmorganca ollama https img shields io github stars jmorganca ollama svg style social get up and running with large language models locally sense2vec https github com explosion sense2vec https img shields io github stars explosion sense2vec svg style social a pytorch library that allows for training and using sense2vec models which are models that leverage the same approach than word2vec but also leverage part of speech attributes for each token which allows it to be meaning aware sentence transformers https github com ukplab sentence transformers https img shields io github stars ukplab sentence transformers svg style social sentence transformers provides an easy method to compute dense vector representations for sentences paragraphs and images spacy https github com explosion spacy https img shields io github stars explosion spacy svg style social industrial strength natural language processing library built with python and cython by the explosion ai team stablelm https github com stability ai stablelmy https img shields io github stars stability ai stablelmy svg style social stability ai language models tensorflow lingvo https github com tensorflow lingvo https img shields io github stars tensorflow lingvo svg style social a framework https blog tensorflow org 2019 02 lingvo tensorflow framework for sequence modeling html for building neural networks in tensorflow particularly sequence models tensorflow text https github com tensorflow text https img shields io github stars tensorflow text svg style social tensorflow text provides a collection of text related classes and ops ready to use with tensorflow 2 0 transformers https github com huggingface transformers https img shields io github stars huggingface transformers svg style social huggingface s library of state of the art pretrained models for natural language processing nlp trlx https github com carperai trlx https img shields io github stars carperai trlx svg style social trlx is a distributed training framework designed from the ground up to focus on fine tuning large language models with reinforcement learning using either a provided reward function or a reward labeled dataset youtokentome https github com vkcom youtokentome https img shields io github stars vkcom youtokentome svg style social youtokentome is an unsupervised text tokenizer focused on computational efficiency it currently implements fast byte pair encoding https arxiv org abs 1508 07909 bpe industry strength rl acme https github com deepmind acme https img shields io github stars deepmind acme svg style social acme is a library of reinforcement learning rl building blocks that strives to expose simple efficient and readable agents ai optimizer https github com tju drl lab ai optimizer https img shields io github stars tju drl lab ai optimizer svg style social ai optimizer is a next generation deep reinforcement learning suit providing rich algorithm libraries ranging from model free to model based rl algorithms from single agent to multi agent algorithms moreover ai optimizer contains a flexible and easy to use distributed training framework for efficient policy training alf https github com horizonrobotics alf https img shields io github stars horizonrobotics alf svg style social alf is a reinforcement learning framework emphasizing on the flexibility and easiness of implementing complex algorithms involving many different components alpacafarm https github com tatsu lab alpaca farm https img shields io github stars tatsu lab alpaca farm svg style social alpacafarm is a simulation framework for methods that learn from human feedback citylearn https github com intelligent environments lab citylearn https img shields io github stars intelligent environments lab citylearn svg style social citylearn is an open source openai gym environment for the implementation of multi agent reinforcement learning rl for building energy coordination and demand response in cities cleanrl https github com vwxyzjn cleanrl https img shields io github stars vwxyzjn cleanrl svg style social cleanrl is a deep reinforcement learning library that provides high quality single file implementation with research friendly features the implementation is clean and simple yet we can scale it to run thousands of experiments using aws batch compilergym https github com facebookresearch compilergym https img shields io github stars facebookresearch compilergym svg style social compilergym is a library of easy to use and performant reinforcement learning environments for compiler tasks d3rlpy https github com takuseno d3rlpy https img shields io github stars takuseno d3rlpy svg style social d3rlpy is an offline deep reinforcement learning library for practitioners and researchers diambra https github com diambra arena https img shields io github stars diambra arena svg style social diambra arena is a software package featuring a collection of high quality environments for reinforcement learning research and experimentation dopamine https github com google dopamine https img shields io github stars google dopamine svg style social dopamine is a research framework for fast prototyping of reinforcement learning algorithms it aims to fill the need for a small easily grokked codebase in which users can freely experiment with wild ideas speculative research evotorch https github com nnaisense evotorch https img shields io github stars nnaisense evotorch svg style social evotorch is an open source evolutionary computation library developed at nnaisense built on top of pytorch finrl https github com ai4finance foundation finrl https img shields io github stars ai4finance foundation finrl svg style social finrl is the first open source framework to demonstrate the great potential of financial reinforcement learning garage https github com rlworkgroup garage https img shields io github stars rlworkgroup garage svg style social garage is a toolkit for developing and evaluating reinforcement learning algorithms and an accompanying library of state of the art implementations built using that toolkit gymnasium https github com farama foundation gymnasium https img shields io github stars farama foundation gymnasium svg style social gymnasium is an open source python library for developing and comparing reinforcement learning algorithms by providing a standard api to communicate between learning algorithms and environments as well as a standard set of environments compliant with that api gymnasium robotics https github com farama foundation gymnasium robotics https img shields io github stars farama foundation gymnasium robotics svg style social gymnasium robotics contains a collection of reinforcement learning robotic environments that use the gymansium api the environments run with the mujoco physics engine and the maintained mujoco python bindings jumanji https github com instadeepai jumanji https img shields io github stars instadeepai jumanji svg style social jumanji is a suite of reinforcement learning rl environments written in jax providing clean hardware accelerated environments for industry driven research malib https github com sjtu marl malib https img shields io github stars sjtu marl malib svg style social malib is a parallel framework of population based learning nested with reinforcement learning methods malib provides higher level abstractions of marl training paradigms which enables efficient code reuse and flexible deployments on different distributed computing paradigms marllib https github com replicable marl marllib https img shields io github stars replicable marl marllib svg style social marllib is a comprehensive multi agent reinforcement learning algorithm library based on rllib it provides marl research community with a unified platform for building training and evaluating marl algorithms mava https github com instadeepai mava https img shields io github stars instadeepai mava svg style social mava is a framework for distributed multi agent reinforcement learning in jax melting pot https github com deepmind meltingpot https img shields io github stars deepmind meltingpot svg style social melting pot is a suite of test scenarios for multi agent reinforcement learning metadrive https github com metadriverse metadrive https img shields io github stars metadriverse metadrive svg style social metadrive is a driving simulator that composes diverse driving scenarios for generalizable rl minigrid https github com farama foundation minigrid https img shields io github stars farama foundation minigrid svg style social the minigrid library contains a collection of discrete grid world environments to conduct research on reinforcement learning the environments follow the gymnasium standard api and they are designed to be lightweight fast and easily customizable minihack https github com facebookresearch minihack https img shields io github stars facebookresearch minihack svg style social minihack is a sandbox framework for easily designing rich and diverse environments for reinforcement learning miniworld https github com farama foundation miniworld https img shields io github stars farama foundation miniworld svg style social miniworld is a minimalistic 3d interior environment simulator for reinforcement learning robotics research ml agents https github com unity technologies ml agents https img shields io github stars unity technologies ml agents svg style social ml agents is an open source project that enables games and simulations to serve as environments for training intelligent agents mushroomrl https github com mushroomrl mushroom rl https img shields io github stars mushroomrl mushroom rl svg style social mushroomrl is a python reinforcement learning rl library whose modularity allows to easily use well known python libraries for tensor computation e g pytorch tensorflow and rl benchmarks e g openai gym pybullet deepmind control suite parl https github com paddlepaddle parl https img shields io github stars paddlepaddle parl svg style social parl is a flexible and high efficient reinforcement learning framework pettingzoo https github com farama foundation pettingzoo https img shields io github stars farama foundation pettingzoo svg style social pettingzoo is a python library for conducting research in multi agent reinforcement learning akin to a multi agent version of gymnasium rllib https github com ray project ray tree master rllib https img shields io github stars ray project ray svg style social rllib is an open source library for reinforcement learning rl offering support for production level highly distributed rl workloads while maintaining unified and simple apis for a large variety of industry applications rlmeta https github com facebookresearch rlmeta https img shields io github stars facebookresearch rlmeta svg style social rlmeta is a flexible lightweight research framework for distributed reinforcement learning based on pytorch and moolib safety gymnasium https github com pku alignment safety gymnasium https img shields io github stars pku alignment safety gymnasium svg style social safety gymnasium is a highly scalable and customizable safe reinforcement learning environment library skrl https github com toni sm skrl https img shields io github stars toni sm skrl svg style social skrl is an open source modular library for reinforcement learning written in python using pytorch and designed with a focus on readability simplicity and transparency of algorithm implementation stable baselines https github com dlr rm stable baselines3 https img shields io github stars dlr rm stable baselines3 svg style social a fork of openai baselines implementations of reinforcement learning algorithms supersuit https github com farama foundation supersuit https img shields io github stars farama foundation supersuit svg style social supersuit introduces a collection of small functions which can wrap reinforcement learning environments to do preprocessing microwrappers tf agents https github com tensorflow agents https img shields io github stars tensorflow agents svg style social a reliable scalable and easy to use tensorflow library for contextual bandits and reinforcement learning industry strength visualisation altair https github com altair viz altair altair is a declarative statistical visualization library for python apache echarts https github com apache echarts apache echarts is a powerful interactive charting and data visualization library for browser bokeh https github com bokeh bokeh https img shields io github stars bokeh bokeh svg style social bokeh is an interactive visualization library for python that enables beautiful and meaningful visual presentation of data in modern web browsers geoplotlib https github com andrea cuttone geoplotlib https img shields io github stars andrea cuttone geoplotlib svg style social geoplotlib is a python toolbox for visualizing geographical data and making maps ggplot2 https github com tidyverse ggplot2 https img shields io github stars tidyverse ggplot2 svg style social an implementation of the grammar of graphics for r gradio https github com gradio app gradio https img shields io github stars gradio app gradio svg style social quickly create and share demos of models by only writing python debug models interactively in your browser get feedback from collaborators and generate public links without deploying anything kangas https github com comet ml kangas https img shields io github stars comet ml kangas svg style social kangas is a tool for exploring analyzing and visualizing large scale multimedia data it provides a straightforward python api for logging large tables of data along with an intuitive visual interface for performing complex queries against your dataset matplotlib https github com matplotlib matplotlib https img shields io github stars matplotlib matplotlib svg style social a python 2d plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms missingno https github com residentmario missingno https img shields io github stars residentmario missingno svg style social missingno provides a small toolset of flexible and easy to use missing data visualizations and utilities that allows you to get a quick visual summary of the completeness or lack thereof of your dataset pdpbox https github com saucecat pdpbox https img shields io github stars saucecat pdpbox svg style social this repository is inspired by icebox the goal is to visualize the impact of certain features towards model prediction for any supervised learning algorithm perspective https github com finos perspective https img shields io github stars finos perspective svg style social streaming pivot visualization via webassembly pixiedust https github com pixiedust pixiedust https img shields io github stars pixiedust pixiedust svg style social pixiedust is a productivity tool for python or scala notebooks which lets a developer encapsulate business logic into something easy for your customers to consume plotly https github com plotly plotly py https img shields io github stars plotly plotly py svg style social an interactive open source and browser based graphing library for python pycebox https github com austinrochford pycebox https img shields io github stars austinrochford pycebox svg style social python individual conditional expectation plot toolbox pygal https github com kozea pygal https img shields io github stars kozea pygal svg style social pygal is a dynamic svg charting library written in python redash https github com getredash redash https img shields io github stars getredash redash svg style social redash is anopen source visualisation framework that is built to allow easy access to big datasets leveraging multiple backends seaborn https github com mwaskom seaborn https img shields io github stars mwaskom seaborn svg style social seaborn is a python visualization library based on matplotlib it provides a high level interface for drawing attractive statistical graphics spotlight https github com renumics spotlight https img shields io github stars renumics spotlight svg style social spotlight helps you to identify critical data segments and model failure modes it enables you to build and maintain reliable machine learning models by curating high quality datasets streamlit https github com streamlit streamlit https img shields io github stars streamlit streamlit svg style social streamlit lets you create apps for your machine learning projects with deceptively simple python scripts it supports hot reloading so your app updates live as you edit and save your file superset https github com apache superset https img shields io github stars apache superset svg style social a modern enterprise ready business intelligence web application tensorboardx https github com lanpa tensorboardx https img shields io github stars lanpa tensorboardx svg style social write tensorboard events with simple function call tensorboard https github com tensorflow tensorboard https img shields io github stars tensorflow tensorboard svg style social a visualization toolkit for machine learning experimentation that makes it easy to host track and share ml experiments yellowbrick https github com districtdatalabs yellowbrick https img shields io github stars districtdatalabs yellowbrick svg style social yellowbrick is a matplotlib based model evaluation plots for scikit learn and other machine learning libraries industry strength recsys easyrec https github com alibaba easyrec https img shields io github stars alibaba easyrec svg style social easyrec is a framework for large scale recommendation algorithms gorse https github com gorse io gorse https img shields io github stars gorse io gorse svg style social gorse aims to be a universal open source recommender system that can be quickly introduced into a wide variety of online services implicit https github com benfred implicit https img shields io github stars benfred implicit svg style social implicit provides fast python implementations of several different popular recommendation algorithms for implicit feedback datasets lightfm https github com lyst lightfm https img shields io github stars lyst lightfm svg style social lightfm is a python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback nvtabular https github com nvidia merlin nvtabular https img shields io github stars nvidia merlin nvtabular svg style social nvtabular is a feature engineering and preprocessing library for tabular data that is designed to easily manipulate terabyte scale datasets and train deep learning dl based recommender systems merlin https github com nvidia merlin merlin https img shields io github stars nvidia merlin merlin svg style social nvidia merlin is an open source library providing end to end gpu accelerated recommender systems from feature engineering and preprocessing to training deep learning models and running inference in production surprise https github com nicolashug surprise https img shields io github stars nicolashug surprise svg style social surprise is a python scikit for building and analyzing recommender systems that deal with explicit rating data industry strength benchmarking and evaluation big bench https github com google big bench https img shields io github stars google big bench svg style social the beyond the imitation game benchmark big bench is a collaborative benchmark intended to probe large language models and extrapolate their future capabilities d4rl https github com farama foundation d4rl https img shields io github stars farama foundation d4rl svg style social d4rl is an open source benchmark for offline reinforcement learning evademl https github com mzweilin evademl zoo https img shields io github stars mzweilin evademl zoo svg style social a benchmarking and visualization tool for adversarial ml evalai https github com cloud cv evalai https img shields io github stars cloud cv evalai svg style social evalai is an open source platform for evaluating and comparing ai algorithms at scale evals https github com openai evals https img shields io github stars openai evals svg style social evals is a framework for evaluating openai models and an open source registry of benchmarks evaluate https github com huggingface evaluate https img shields io github stars huggingface evaluate svg style social evaluate is a library that makes evaluating and comparing models and reporting their performance easier and more standardized helm https github com stanford crfm helm https img shields io github stars stanford crfm helm svg style social holistic evaluation of language models helm is a benchmark framework to increase the transparency of language models lucid https github com tensorflow lucid https img shields io github stars tensorflow lucid svg style social lucid is a collection of infrastructure and tools for research in neural network interpretability meta world https github com farama foundation metaworld https img shields io github stars farama foundation metaworld svg style social meta world is an open source simulated benchmark for meta reinforcement learning and multi task learning consisting of many distinct robotic manipulation tasks omnisafe https github com pku marl omnisafe https img shields io github stars pku marl omnisafe svg style social omnisafe is a comprehensive and reliable benchmark for safe reinforcement learning covering a multitude of saferl domains and delivering a new suite of testing environments opencv zoo and benchmark https github com opencv opencv zoo https img shields io github stars opencv opencv zoo svg style social a zoo for models tuned for opencv dnn with benchmarks on different platforms overcooked ai https github com humancompatibleai overcooked ai https img shields io github stars humancompatibleai overcooked ai svg style social overcooked ai is a benchmark environment for fully cooperative human ai task performance based on the wildly popular video game overcooked recommenders https github com microsoft recommenders https img shields io github stars microsoft recommenders svg style social recommenders contains benchmark and best practices for building recommendation systems provided as jupyter notebooks rlexplore https github com yuanmingqi rl exploration baselines https img shields io github stars yuanmingqi rl exploration baselines svg style social rlexplore provides stable baselines of exploration methods in reinforcement learning safepo baselines https github com pku marl safe policy optimization https img shields io github stars pku marl safe policy optimization svg style social safepo baselines is a benchmark repository for safe reinforcement learning algorithms commercial platform amazon web services https aws amazon com aws amazon web services is a comprehensive evolving cloud computing platform provided by amazon that includes a mixture of infrastructure as a service iaas platform as a service paas and packaged software as a service saas offerings including amazon augmented ai https aws amazon com augmented ai amazon rekognition https aws amazon com rekognition amazon sagemaker https aws amazon com sagemaker anthropic https www anthropic com anthropic is an ai safety and research company that s working to build reliable interpretable and steerable ai systems anyscale https www anyscale com anyscale is a unified compute platform that makes it easy to develop deploy and manage scalable ai and python applications using ray apheris https www apheris com a platform for federated and privacy preserving data science that lets you securely collaborate on ai with partners without sharing any data aporia https aporia com the ml observability platform empowers data science and ml teams to maintain exceptional model performance while effectively scaling their production ml systems aporia offers versatile tools designed to support any ml use case enabling users to customize model tracking dashboard visualization reporting and metrics to suit the unique requirements of ml professionals the aporia platform allows ml practitioners to monitor their entire dataset without duplicating production data efficiently identifying issues such as drift bias model deterioration and performance and data integrity issues arize https arize com ml observability and automated model monitoring to help ml practitioners understand how their models perform in production troubleshoot issues and improve model performance ml teams can upload offline training or validation baselines into an evaluation inference store alongside online production data for model validation drift detection data quality checks and model performance management arthur https arthur ai authur is a platform that measures monitors and improves machine learning models to deliver better results azure machine learning https azure microsoft com en us products machine learning azure machine learning empowers data scientists and developers to build deploy and manage high quality models faster and with confidence bigml https bigml com a consumable programmable and scalable machine learning platform that makes it easy to solve and automate classification regression time series etc censius https censius ai censius is an ai observability platform that assists enterprises in continuously monitoring analyzing and explaining their production models it combines monitoring accountability and explainability into one observability platform cerebras https www cerebras net cerebras builds computer systems for complex artificial intelligence deep learning applications cnvrg io https cnvrg io an end to end platform to manage build and automate machine learning comet http comet ml machine learning experiment management free for open source and students video https www youtube com watch v xaybrkapene d2iq kaptain https d2iq com products kaptain an end to end machine learning platform built for security scale and speed that allows enterprises to develop and deploy machine learning models that runs in the cloud on premises incl air gapped in hybrid environments or on the edge based on kubeflow and open source kubernetes universal declarative operators https kudo dev kudo dagshub https dagshub com community platform for open source ml manage experiments data models and create collaborative ml projects easily databricks https www databricks com an integrated end to end machine learning environment incorporating managed services for experiment tracking model training feature development and management and feature and model serving dataiku https www dataiku com collaborative data science platform powering both self service analytics and the operationalization of machine learning models in production datarobot https www datarobot com automated machine learning platform which enables users to build and deploy machine learning models datatron https datatron com machine learning model governance platform for all your ai models in production for large enterprises deep cognition deep learning studio https deepcognition ai e2e platform for deep learning deepsense ai https deepsense ai deepsense ai helps companies gain competitive advantage by providing customized ai powered end to end solutions with the main focus on ai software team augmentation and ai advisory diffgram https diffgram com training data first platform database training data pipelines for supervised ai integrated with gcp aws azure and top annotation supervision uis or use built in diffgram ui or build your own plus a growing list of integrated service providers for computer vision nlp and supervised deep learning machine learning domino https www dominodatalab com an enterprise mlops platform that supports data scientist collaboration with their preferred tools languages and infrastructure with it central resource management governance and security without vendor lock in fennel https fennel ai realtime feature engineering platform for fast moving machine learning teams python pandas native built in rust easy to install use run builds upon best practices for reducing data feature quality issues and keeps cloud spend low fully managed zero ops fiddler https www fiddler ai fiddler is a model performance management platform that offers model monitoring observability explainability fairness google cloud machine learning engine https cloud google com ml engine managed service that enables developers and data scientists to build and bring machine learning models to production graphsignal https graphsignal com machine learning profiler that helps make model training and inference faster and more efficient h2o driverless ai https www h2o ai products h2o driverless ai automates key machine learning tasks delivering automatic feature engineering model validation model tuning model selection and deployment machine learning interpretability bring your own recipe time series and automatic pipeline generation for model scoring video https www youtube com watch v zqcofp3 rgc hugging face https huggingface co hugging face is a platform that allows users to share machine learning models and datasets ibm watson studio https www ibm com cloud watson studio build and scale trusted ai on any cloud automate the ai lifecycle for modelops innereye https innereye ai innereye combines human intelligence with artificial intelligence by capitalizing on the merging of human neural processing and deep artificial neural networks innereye allows fast and accurate visual inspection real time ai training and validation and establishes a unique human machine interface for connected user applications iguazio data science platform https www iguazio com bring your data science to life by automating mlops with end to end machine learning pipelines transforming ai projects into real world business outcomes and supporting real time performance at enterprise scale iterative studio https studio iterative ai seamless data and model management experiment tracking visualization and automation with git as the single source of truth kaggle https www kaggle com kaggle offers machine learning and data science competitions as well as offering a public data and cloud based business platform for data science and ai education katonic ai https katonic ai automate your cycle of intelligence with katonic mlops platform kern ai https www kern ai kern ai builds the self service development environment for nlp training data used by data scientists to quickly build high quality large scale labeled datasets labelbox https labelbox com image labelling service with support for semantic segmentation brush superpixels bounding boxes and nested classifications modelop https www modelop com an enterprise mlops platform that automates the governance management and monitoring of deployed ai ml models across platforms and teams resulting in reliable compliant and scalable ai initiatives modelplace https modelplace ai modelplace provides a directory of tested and benchmarked ai models from around the world curated by opencv mljar https mljar com platform for rapid prototyping developing and deploying machine learning models neptune ai https github com neptune ai neptune client https img shields io github stars neptune ai neptune client svg style social neptune is a lightweight solution designed for 1 experiment tracking 2 model registry 3 ml runs live monitoring nimblebox https nimblebox ai a full stack mlops platform designed to help data scientists and machine learning practitioners around the world discover create and launch multi cloud apps from their web browser octoml https octoml ai octoml makes ai more sustainable through efficient model execution and automation to scale services and reduce engineering burden openai https openai com openai aims to promote and develop friendly ai in a way that benefits humanity as a whole pinecone https www pinecone io pinecone vector database makes it easy to build high performance vector search applications prodigy https prodi gy prodigy is a scriptable annotation tool so efficient that data scientists can do the annotation themselves enabling a new level of rapid iteration rapidminer https rapidminer com rapidminer is the enterprise ready data science platform that amplifies the collective impact of your people expertise and data for breakthrough competitive advantage replicate https replicate com replicate lets you run machine learning models with a cloud api without having to understand the intricacies of machine learning or manage your own infrastructure robust intelligence https www robustintelligence com robust intelligence is an end to end ml integrity solution that proactively eliminates failure at every stage of the model lifecycle from pre deployment vulnerability detection and validation to post deployment monitoring and protection robust intelligence gives teams the confidence to scale models in production across a variety of use cases and modalities scale https scale com scale ai turns raw data into high quality training data by combining machine learning powered pre labeling and active tooling with varying levels and types of human review scribble enrich https www scribbledata io product customizable auditable privacy aware feature store it is designed to help mid sized data teams gain trust in the data that they use for training and analysis and support emerging needs such drift computation and bias assessment sigopt https sigopt com sigopt is a model development platform that makes it easy to track runs visualize training and scale hyperparameter optimization for any type of model built with any library on any infrastructure skymind https skymind global software distribution designed to help enterprise it teams manage deploy and retrain machine learning models at scale skytree http skytree net end to end machine learning platform video https www youtube com watch v xucwpnu f1k superannotate https www superannotate com a complete set of solutions for image and video annotation and an annotation service with integrated tooling on demand narrow expertise in various fields and a custom neural network automation and training models powered by ai superb ai https superb ai com ml dataops platform providing various tools to build label manage and iterate on training data syndicai https syndicai co easy to use cloud agnostic platform that deploys manages and scales any trained ai model in minutes with no configuration infrastructure setup talend studio https www talend com data integration platform that provides various software and services for data integration data management enterprise application integration data quality cloud storage and big data tecton https www tecton ai tecton is an all in one system to build automate and centralize feature workflows for production ml valohai https valohai com machine orchestration version control and pipeline management for deep learning vertex ai https cloud google com vertex ai vertex ai workbench is the single environment for data scientists to complete all of their ml work from experimentation to deployment to managing and monitoring models it is a jupyter based fully managed scalable enterprise ready compute infrastructure with security controls and user management capabilities ultralytics https ultralytics com ultralytics simplifies data sourcing labeling model training and deployment services that offer artificial intelligence weights biases https github com wandb wandb https img shields io github stars wandb wandb svg style social machine learning experiment tracking dataset versioning hyperparameter search visualization and collaboration whylabs https whylabs ai enable observability to detect data and ml issues faster deliver continuous improvements and avoid costly incidents zilliz https zilliz com zilliz builds vector database to accelerate development of next generation data fabric | machine-learning mlops interpretability explainability responsible-ai deep-learning machine-learning-operations ml-ops ml-operations privacy-preserving privacy-preserving-ml privacy-preserving-machine-learning data-mining large-scale-ml production-ml large-scale-machine-learning production-machine-learning awesome awesome-list | ai |
awesome-korean-llm | awesome korean llm awesome https awesome re badge svg https awesome re llm awesome list llm polyglot ko https github com eleutherai polyglot 1 3b 3 8b 5 8b 12 8b eleutherai https github com eleutherai gpt neox huggingface https huggingface co eleutherai polyglot ko 12 8b tree main koalpaca https github com beomi koalpaca 7b 13b 30b 65b 5 8b 12 8b beomi https github com beomi llama polyglot ko huggingface https huggingface co beomi koalpaca polyglot 12 8b kullm https github com nlpai lab kullm 5 8b 12 8b https github com nlpai lab polyglot ko huggingface https huggingface co nlpai lab kullm polyglot 12 8b v2 korani https github com krafton ai korani 13b 12 8b krafton https github com krafton ai llama polyglot ko huggingface https huggingface co krafton korani v3 13b k g oat https github com marker inc korea k g oat 5 8b marker inc https github com marker inc korea polyglot ko huggingface https huggingface co dopeornope koat 5 8b tree main kovicuna https github com melodysdreamj kovicuna 7b melodysdreamj https github com melodysdreamj vicuna 7b huggingface https huggingface co junelee ko vicuna 7b kollama https huggingface co beomi kollama 33b 7b 13b 33b beomi https github com beomi llama huggingface https huggingface co beomi kollama 33b llama 2 ko https huggingface co beomi llama 2 ko 7b 7b 70b beomi https github com beomi llama 2 huggingface https huggingface co beomi llama 2 ko 7b kollama2 https github com psymon dev kollama2 psymon dev https github com psymon dev llama 2 huggingface https huggingface co psymon kollama2 7b komt https github com davidkim205 komt 7b 13b davidkim205 https github com davidkim205 llama 2 huggingface https huggingface co davidkim205 komt llama 2 13b hf llama 2 korean https huggingface co quantumaikr llama 2 70b fb16 korean 7b 13b 70b https github com quantumaikr llama 2 huggingface https huggingface co quantumaikr llama 2 70b fb16 korean koreanlm https github com quantumaikr koreanlm 1 5b 3b https github com quantumaikr huggingface https huggingface co quantumaikr koreanlm kormkv https huggingface co beomi korwkv 1 5b 1 5b 6b beomi https github com beomi rmkvv4 huggingface https huggingface co beomi korwkv 1 5b koalpaca kormkv https huggingface co beomi koalpaca korwkv 6b 1 5b 6b beomi https github com beomi kormkv huggingface https huggingface co beomi korwkv 1 5b kogpt https github com kakaobrain kogpt 6b https github com kakaobrain huggingface https huggingface co kakaobrain kogpt tree kogpt6b ryan1 5b kogpt2 https github com skt ai kogpt2 1 5b skt https github com skt ai gpt 2 llama 2 ko 7b chat https huggingface co kfkas llama 2 ko 7b chat 7b taemin6697 https github com taemin6697 llama 2 huggingface https huggingface co kfkas llama 2 ko 7b chat 42dot llm plm 1 3b https huggingface co 42dot 42dot llm plm 1 3b 1 3b 42dot https github com 42dot llama 2 huggingface https huggingface co 42dot 42dot llm plm 1 3b 42dot llm sft 1 3b https huggingface co 42dot 42dot llm sft 1 3b 1 3b 42dot https github com 42dot llama 2 huggingface https huggingface co 42dot 42dot llm sft 1 3b ko platypus https github com marker inc korea ko platypus 7b marker inc https github com marker inc korea llama 2 huggingface https huggingface co kyujinpy ko platypus2 7b ex sitebunny https huggingface co 42maru sitebunny 13b 13b 42maru https huggingface co 42maru llama 2 huggingface https huggingface co 42maru sitebunny 13b chatskku https huggingface co jojo0217 chatskku5 8b 5 8b jojo0217 https github com jojo0217 polyglot ko huggingface https huggingface co jojo0217 chatskku5 8b nallm https github com nara information na llm 1 3b 3 8b https github com nara information polyglot ko huggingface https huggingface co nara lab nallm polyglot ko 3 8b base llm 1 polyglot ko polyglot ko https github com eleutherai polyglot koalpaca https github com beomi koalpaca kullm https github com nlpai lab kullm korani https github com krafton ai korani k g oat https github com marker inc korea k g oat chatskku https huggingface co jojo0217 chatskku5 8b nallm https github com nara information na llm 2 1 llama kollama https huggingface co beomi kollama 33b koalpaca https github com beomi koalpaca korani https github com krafton ai korani 2 2 llama 2 llama 2 ko https huggingface co beomi llama 2 ko 7b komt https github com davidkim205 komt llama 2 korean https huggingface co quantumaikr llama 2 70b fb16 korean llama 2 ko 7b chat https huggingface co kfkas llama 2 ko 7b chat 42dot llm plm 1 3b https huggingface co 42dot 42dot llm plm 1 3b 42dot llm sft 1 3b https huggingface co 42dot 42dot llm sft 1 3b ko platypus https github com marker inc korea ko platypus sitebunny https huggingface co 42maru sitebunny 13b 3 kovicuna https github com melodysdreamj kovicuna kormkv https huggingface co beomi korwkv 1 5b koalpaca kormkv https huggingface co beomi koalpaca korwkv 6b kogpt https github com kakaobrain kogpt kogpt2 https github com skt ai kogpt2 koreanlm https github com quantumaikr koreanlm contributing llm pr | ai |
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mds-docs | p align center a href img alt src https innovaccer com static image site logo innovaccer logo black svg width 20 a p h1 align center masala design system h1 h3 align center gatsby site for masala design system documentation h3 get up and running bash yarn yarn develop | hacktoberfest hacketoberfest2021 design-system | os |
vuedarkmode | p align center style background 1b2431 padding 20px 0 a href https www growthbunker dev vuedarkmode target blank img width 100 src https raw githubusercontent com growthbunker vuedarkmode master src images vuedarkmode jpg a p npm https img shields io npm v growthbunker vuedarkmode svg https www npmjs com package growthbunker vuedarkmode npm https img shields io npm dm growthbunker vuedarkmode svg https npm stat com charts html package growthbunker vuedarkmode average time to resolve an issue http isitmaintained com badge resolution growthbunker vuedarkmode svg http isitmaintained com project growthbunker vuedarkmode average time to resolve an issue percentage of issues still open http isitmaintained com badge open growthbunker vuedarkmode svg http isitmaintained com project growthbunker vuedarkmode percentage of issues still open github license https img shields io badge license mit blue svg https github com growthbunker vuedarkmode blob master license netlify status https api netlify com api v1 badges ae3d4112 1c84 4868 b4eb 271c3136ede6 deploy status https app netlify com sites growthbunker deploys documentation you can browse the documentation for vue dark mode on the website https www growthbunker dev vuedarkmode installation npm install growthbunker vuedarkmode or if you prefer using yarn yarn add growthbunker vuedarkmode vue js in your main js file js import vue from vue import vuedarkmode from growthbunker vuedarkmode vue use vuedarkmode nuxt js create a new plugin in plugins vuedarkmode js js import vue from vue import vuedarkmode from growthbunker vuedarkmode vue use vuedarkmode add this new plugin to nuxt config js js module exports plugins src plugins vuedarkmode js cdn get the latest version from jsdelivr https www jsdelivr com and import the javascript file in your page html script src https cdn jsdelivr net npm vue 2 5 dist vue min js script script src https cdn jsdelivr net npm growthbunker vuedarkmode latest dist vuedarkmode min js script we recommend our users to lock vue dark mode s version when using cdn requesting the latest version as opposed to latest major or latest minor is dangerous because major versions usually come with breaking changes only do this if you really know what you are doing please refer to jsdelivr com https www jsdelivr com features for more information available components we are releasing new components on a monthly basis subscribe to our newsletter http eepurl com dllkbm to stay in touch with coming releases base components basealert documentation https www growthbunker dev vuedarkmode basealert source code src components base basealert vue baseavatar documentation https www growthbunker dev vuedarkmode baseavatar source code src components base baseavatar vue basebadge documentation https www growthbunker dev vuedarkmode basebadge source code src components base basebadge vue basebutton documentation https www growthbunker dev vuedarkmode basebutton source code src components base 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than welcome to contribute to vue dark mode just submit changes via pull request and i will review them before merging 1 fork it 2 create your feature branch git checkout b my new feature 3 commit your changes git commit am add some feature 4 push to the branch git push origin my new feature 5 submit a pull request the documentation is available in the docs folder the vue dark mode components are available in the lib folder license vue dark mode is mit licensed license cross browsing vue dark mode is using browserstack https www browserstack com to make sure our components render properly on modern browsers img alt browserstack logo width 200px src https raw githubusercontent com growthbunker vuedarkmode master src images browserstack png | vuejs design-system components bootstrap darkmode nuxtjs | os |
AV-Game-of-Deep-Learning | av game of deep learning analyticsvidhya game of deep learning computer vision hackathon competition banner images banner jpg competition link https datahack analyticsvidhya com contest game of deep learning problem statement ship or vessel detection has a wide range of applications in the areas of maritime safety fisheries management marine pollution defence and maritime security protection from piracy illegal migration etc keeping this in mind a governmental maritime and coastguard agency is planning to deploy a computer vision based automated system to identify ship type only from the images taken by the survey boats you have been hired as a consultant to build an efficient model for this project there are 5 classes of ships to be detected which are as follows category images category png dataset description there are 6252 images in train and 2680 images in test data the categories of ships and their corresponding codes in the dataset are as follows cargo 1 military 2 carrier 3 cruise 4 tankers 5 there are three files provided to you viz train zip test csv and sample submission csv which have the following structure variable definition image name of the image in the dataset id column category ship category code target column train zip contains the images corresponding to both train and test set along with the true labels for train set images in train csv evaluation metric the evaluation metric for this competition is weighted f1 score public and private split public leaderboard is based on randomly selected 30 of the test images while private leaderboard will be evaluated on remaining 70 of the test images python 3 6 libraries fastai 1 0 51 torch 1 0 1 torchvision 0 2 2 pretrainedmodels approach i have used fastai https fast ai cnn learner datablock api the final submission is a result of votings based on 22 submissions which were created from 22 different models based on different techniques such as different image size 299 484 599 different pre trained architectures resnet101 resnet152 densenet161 densenet169 different augmentation techniques mixup models see the code for details score public lb score 0 9906 rank 2 2083 private lb score 0 9875 rank 1 2083 final thoughts although training 22 models seems very time consuming as well as computationally intensive but for small dataset like this it would be a great idea i was able to acheive private lb score similar upto 4 decimal places as the score from 22 models using only 9 models including 4 mixup models image size was fixed at 499x499 4 pre trained architectures stated above were used and lastly voting method was applied however the public score was not that great 0 9855 this suggests that we still can achieve state of the art results by training fewer models and applying right ensemble method for aggregating | ai |
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sql-challenge | sql challenge data modeling data engineering and data analysis of a historical employee database using postgresql by jason estrada part 1 data modeling in order to answer questions based on people the company employed during the 1980s and 1990s data exploration of six csv files was performed and an entity relationship diagram erd was created to establish relationships across the files quickdbd https app quickdatabasediagrams com was used and a visual representation can be seen below erd employeesql quickdbd erd png part 2 data engineering once modeled a table schema employeesql schema sql was created in postgresql and each csv file was imported to their corresponding table part 3 data analysis eight questions were answered using joins filters and aggregate functions query employeesql data analysis queries sql a jupyter notebook file was also created to capture notes while working through the project | server |
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IntroToComputerVision | intro to computer vision udacity ud810 lecture slides problem sets and c solutions to ud810 original google doc https docs google com spreadsheets d 1ecugiyhyofqpi3hpxb 7nndrlgpx zgkwsqzfqhpaus pubhtml with problem sets and slides miscellaneous images http sipi usc edu database database php volume misc from usc computer vision image database http homepages inf ed ac uk rbf cvonline imagedbase htm from the university of edinburgh prerequisites i try to accelerate all of the assignments with cuda so you will need an nvidia gpu along with cuda toolkit installed this repository is developed on ubuntu 17 10 cuda 9 1 intel core i7 6800k geforce gtx 1080 you will need cuda follow nvidia s cuda installation instructions http docs nvidia com cuda cuda installation guide linux index html to install git lfs https git lfs github com is required to clone the images and lecture slides from here there are two options building in docker or just building locally on a host machine containerized build in docker recommended this is the suggested approach to building this project since all of the dependencies are included in the docker image install docker ce as described for your distribution on the docker docs https docs docker com install follow the optional linux post installation https docs docker com install linux linux postinstall steps to run docker without sudo install nvidia docker2 as described in the nvidia docker docs https github com nvidia nvidia docker wiki installation version 2 0 the container provided in this repo needs the nvidia docker runtime to run clone this repo and build run the docker container bash git clone recursive https github com tanmaniac introtocomputervision git cd introtocomputervision docker build the docker container build sh run the container run sh this will drop you into a shell where you can follow the build steps below the introtocomputervision directory this one is mapped to home introtocomputervision in the docker container build on host build opencv 3 4 1 as directed in the opencv documentation make sure to add the dwith cuda on cmake flag to compile cuda features install eigen http eigen tuxfamily org as described in its documentation gnuplot which you can install from your distro repository on ubuntu bash sudo apt install gnuplot building bash navigate to wherever you cloned this repo first mkdir build cd build cmake make j if you want to use nvidia debugging tools like cuda memcheck or the nvidia visual profiler compile with debug flags bash mkdir build cd build cmake dcmake build type debug make j note that this increases runtime of some kernels by around 100x so only compile in debug mode if you need it running build outputs are placed in the bin directory all of the executables are configured with yaml files in the config directory you can edit these to change the input parameters to each of the assignments for example with problem set 0 all you need to do after building is bash cd bin ps0 | computer-vision ud810 cuda udacity opencv image-processing stereo-vision harris-corners lucas-kanade ransac particle-filter | ai |
React-Redux-Flask | react redux flask boilerplate application for a flask jwt backend and a react redux front end with material ui python 2 7 or 3 x pytest heroku flask react redux react router 2 0 react router redux babel 6 scss processing webpack screenshot http i imgur com zis4qkw png create db sh export database url postgresql username password localhost mydatabase or export database url mysql mysqlconnector username password localhost mydatabase or export database url sqlite your db more about connection strings in this flask config guide http flask sqlalchemy pocoo org 2 1 config python manage py create db python manage py db upgrade python manage py db migrate to update database after creating new migrations use sh python manage py db upgrade install front end requirements sh cd static npm install run back end sh python manage py runserver test back end sh python test py cov report term cov report html cov application tests run front end sh cd static npm start build front end sh npm run build production new to python if you are approaching this demo as primarily a frontend dev with limited or no python experience you may need to install a few things that a seasoned python dev would already have installed most macs already have python 2 7 installed but you may not have pip install you can check to see if you have them installed python version pip version if pip is not installed you can follow this simple article to get both homebrew and python https howchoo com g mze4ntbknjk install pip on mac os x after you install python you can optionally also install python 3 brew install python3 now you can check again to see if both python and pip are installed once pip is installed you can download the required flask modules sudo pip install flask flask script flask migrate flask bcrypt now you can decide on which database you wish to use new to mysql if you decide on mysql install the free community edition of mysql https dev mysql com downloads mysql and mysql workbench https www mysql com products workbench 1 start mysql from the system preferences 2 open mysql workbench and create a database http stackoverflow com questions 5515745 create a new database with mysql workbench called mydatabase but don t create the tables since python will do that for you 3 install the mysql connector for python add the database url configuration and create the database and tables sudo pip install mysql connector python rf export database url mysql mysqlconnector username password localhost mydatabase python manage py create db note you do not need to run python manage py db upgrade or python manage py db migrate if its your first go at it 4 run back end python manage py runserver if all goes well you should see running on http 127 0 0 1 5000 press ctrl c to quit followed by a few more lines in the terminal 5 open a new tab to the same directory and run the front end cd static npm install npm start 6 open your browser to http localhost 3000 register and setup your first account 7 enjoy by this point you should be able to create an account and login without errors | redux react flask material-ui boilerplate-application | front_end |
container_detection | computer vision object detection to detect and count specific objects shipping containers from images and or videos this project is based on chainercv api and single shot multibox detector https github com chainer chainercv tree master examples ssd algorithm the dataset used for training is a mix of coco dataset and manually labeled images using yuyu21 s tool https github com yuyu2172 image labelling tool the reason for this is that my first attempt using only my labeled images was very effective in terms of true positives but was also generating lots of false positives so i had to enrich the datasets for some negative mining labeling labeling is done throug the graphical interface credit to mit https bitbucket org ueacomputervision image labelling tool with the command bash python source flask app py image dir datasets train label names source label names coco container yml file ext jpg training i have been using a redhat 7 4 server with a gpu tesla for the training and have gone through 500k iterations with validation every 1k and decreased learning rate every 100k training is done with the command bash python source examples ssd train py train datasets train lr 0 0001 step size 100000 val datasets validation label source label names coco container yml out models gpu 0 loaderjob 10 iteration 1000000 val iteration 1000 test on images i created a shiny app for the application of the model which calls a python program to display side by side the original image and the result shiny demo https github com laurentberder container detection blob master shiny demo png shiny app test on videos i ve also downloaded a few clips of videos and labeled them since the model used is not very fast it can t be used real time detection takes a couple seconds per images so the script captures all the frames then labels each of them and reconstructs the video from the label frames bash python video label video py video file path to video s to labelize results result video https github com laurentberder container detection blob master video result gif result video | deep-learning chainercv python r shiny video detection label-images computer-vision shipping-containers object-detection bounding-boxes image-processing image-recognition | ai |
weibo_text_mining | weibo text mining apply natural language processing techniques on weibo content analysis what is weibo according to wikipedia sina weibo is a chinese microblogging weibo webiste every day about 100 million messages are posted on sina weibo what is our topic man s brutal beating of female driver divides chinese public after different car videos emerge http www scmp com news china society article 1787577 mans brutal beating female driver divides chinese public after page all our data through weibo api and some web scripping techniques we were able to get about 7000 tweets from may 3rd to june 3rd 2015 on weibo com including usernames ids publish dates and counts of repost like content and etc method supervised learning randomly selected 1 10 tweets from the database and analyze the attitude of the content 1 the woman deserved the beating 2 the man lost his mind read the tweets decided the attitude of the content and skipped the ones with murky attitude eg i think both a and b were wrong but i can t decide who was at more fault data clean got rid of the reposted content in python using functions such as strip split and partition text mining built and compared results from two models we built to text our data decision tree and native bayes result nb had higher accuracy than dt in our case 0 78 0 84 no of train data test data 1 20 splitted the tweets into two datasets based on the publish date and tested again before and after the release of the second video accuracy 0 83 before the 2nd video resleased 0 65 afterwards model application applied the model on 5000 untrained tweets and let the machine predict the attitude of the content result before the second video was released only 3 of people on weibo think that the female driver deserved the beating however the number quickly increased to 61 6 after the second video was released which showed that the female driver s drving dangerously on the high way in front the male driver s car | ai |
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hiproxy | hiproxy img src https avatars0 githubusercontent com u 29273417 v 3 alt hiproxy width 120 height 120 hiproxy is a lightweight web proxy tool based on node js node the primary purpose of hiproxy is to solve the problem of host management and reverse proxy needs of developers for example if you are working as a team and each of the developers in the team need a different proxy setting you will no longer need to modify your hosts file or use a web server like nginx nginx as a reverse proxy hiproxy extends the syntax of hosts file to support port numbers besides hiproxy also supports configuration through a syntax similar to the nginx configuration file nginx config nginx https nginx org nginx config http nginx org en docs beginners guide html nginx beginner s guide node https nodejs org node js https github com hiproxy hiproxy blob master readme zh md build status https travis ci org hiproxy hiproxy svg branch master https travis ci org hiproxy hiproxy build status https ci appveyor com api projects status 0g898oor4o82ah8n branch master svg true https ci appveyor com project zdying hiproxy branch master codecov https codecov io gh hiproxy hiproxy branch master graph badge svg https codecov io gh hiproxy hiproxy js semistandard style https img shields io badge code 20style semistandard brightgreen svg style flat https github com flet semistandard npm https img shields io npm v hiproxy svg https www npmjs com package hiproxy node js version https img shields io badge node 3e 3d0 12 7 green svg https nodejs org license https img shields io badge license mit blue svg https github com hiproxy hiproxy blob master license why hiproxy if you are a front end developer it is not uncommon for you to encounter the following problems debugging web pages locally to develop your web projects in a local development environment you ll have to run a back end server such as a node js express application or a java springboot application as a front end developer you might not be familiar with the back end technology stack simply setting up the development environment can consume a lot of your time cross origin issues while developing your front end projects locally you might need to solve cross domain and cross origin resource sharing issues to address these problems you will need to modify the response header self signed certificates you ll often need to test https pages when you visit https pages with a self signed certificate your browser will raise security warnings one common way to modify the response header is to put a proxy as a man in the middle nginx for example has a nice syntax that you can configure as a reverse proxy to handle all these needs although nginx is a great tool to address all the above problems when setting up nginx you ll also modify your hosts file a lot to proxy the requests to a local nginx service this can especially turn out to be a burden if you are working on multiple projects can we have a better way to solve this problem well yes meet hiproxy features nginx config style configuration file syntax with a simple and intuitive configuration extended hosts configuration with port numbers plugin extensions to rewrite directives command line interface and pages automatic generation and management of tls certificates auto detection of configuration file proxy auto configuration you can run hiproxy as a background service and redirect its output to a log file you can open a browser window and configure your proxy from its web interface hiproxy provides a node js api for fine tuning and lower level control installation bash npm install g hiproxy if you want to experience the latest features of hiproxy you can install the next version npm install g hiproxy next usage cli start proxy server bash hiproxy start p 5525 debug workspace path to workspace configure proxy bash 127 0 0 1 5525 cli usage bash hiproxy help usage hiproxy command option commands start start a local proxy server stop stop the local proxy server only works in daemon mode restart restart the local proxy service only works in daemon mode state show all the servers state only works in daemon mode open open browser and set proxy hello a test command that say hello to you options v version display version information h help display help information log dir dir the log directory when run in background default user home directory log time show time info before every log message log level the log levels format level1 lavel2 grep content filter the log data documentation http hiproxy org note this is an incomplete documentation we are still writing if you are willing to help us write or translate the documentation please contact zdying live com mailto zdying live com steps for contributing documentation the documentation repo is https github com hiproxy documentation choose one of the issues https github com hiproxy hiproxy issues utf8 e2 9c 93 q is 3aissue 20is 3aopen 20 5btranslate 5d and submit a comment that tell others you will translate this part create your own fork https github com hiproxy documentation fork on github translate the md files that you choose you can reaplce the file content to the english version directly submit a pr after you have submitted your pull request we ll try to get back to you as soon as possible we may suggest some changes or improvements wiki https github com hiproxy hiproxy wiki node js api js var server require hiproxy server var proxy new server 8848 10086 events proxy on request function req res req something some thing console log new request req method req url proxy on data function data console log on response data tostring proxy start then function servers console log proxy server started at 127 0 0 1 8848 stop proxy server proxy stop restart proxy server proxy restart hosts configuration example hiproxy supports enhanced version of hosts the hosts file supports not only ip but also port numbers bash comment 127 0 0 1 example com 127 0 0 1 8800 blog example com life example com rewrite configuration example bash set port 8899 set ip 127 0 0 1 set online 210 0 0 0 domain example com location proxy pass http online location blog proxy pass http ip port blog proxy set header from hiproxy set header proxy hiproxy sample project here is an example project that you can play with https github com hiproxy hiproxy example running tests bash npm test contributing please read contributing md https github com hiproxy hiproxy blob master contributing md for details on our code of conduct and the process for submitting pull requests to us authors zdying html javascript css node js developer zdying https github com zdying zhouhailong html javascript css node js developer zhouhailong https github com zhouhailong alfred sang aka i5ting a full stack developer and node js evangelist he works for alibaba group as a principal front end developer and runs a self media on the topic of full stack node js his book the marvelous node js part i was published in july 2019 see also the list of contributors https github com hiproxy hiproxy graphs contributors who participated in this project built with hemsl https www npmjs com package hemsl a lightweight node js command line argv parser and command executor colors https www npmjs com package colors get color and style in your node js console node forge https www npmjs com package node forge javascript implementations of network transports cryptography ciphers pki message digests and various utilities op browser https www npmjs com package op browser open browser window and set proxy os homedir https www npmjs com package os homedir node js 4 os homedir ponyfill url pattern https www npmjs com package url pattern easier than regex string matching patterns for urls and other strings turn strings into data or data into strings simple mime https www npmjs com package simple mime a simple mime database thanks to the authors of the above libraries to provide such a useful library thanks to v0lkan https github com v0lkan jaylee404 https github com jaylee404 jeoxs https github com jeoxs james fancy https segmentfault com u jamesfancy thanks to the above friends to help translate hiproxy documents change log see the changelog md changelog md for details license this project is licensed under the mit license see the license https github com hiproxy hiproxy blob master license file for details code of conduct we are committed to making participation in this project a harassment free experience for everyone regardless of the level of experience gender gender identity and expression sexual orientation disability personal appearance body size race ethnicity age religion or nationality see the code of conduct for details code of conduct md | nodejs proxy nginx reverse-proxy hosts rewrite http https certificate | front_end |
checkout-service | checkout service checkout service for project in cloud virtualization system engineering class autum 2016 at uwt before clone the project make sure you have golang and set up gopath properly more info on how how install and set up https golang org doc install install clone the service repo git clone https github com knguyen6 checkout service git then cd checkout service go install go run main go | cloud |
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Machine-Learning-For-Finance | machine learning for finance 1 regression based machine learning for algorithmic trading machine learning for finance algorithmic trading and investing slides https github com anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading machine 20learning 20 20linear 20regression 20for 20algo 20trading 20v2017 07 13 pdf these set of slides explained the current asset management environment and the advanced of technology on asset management categories of machine and deep learning are explained a brief introduction on linear regression and associated assumptions are covered stylized statistical properties of financial time series and asset returns are presented highlighting the challenges to ease learners to understand machine learning linear regression has been used as the conduit firstly the shortcoming of linear regression is highlighted we then follow by the steps of model building and covering concepts such as hyperparameters cross validation model validation bias variance tradeoff the 6 stages of professional quant strategy is also covered to provide some perspective on where machine learning fits in 1 1 pairs trading machine learning linear regression a walk through on how to design your own pairs trading using linear model https nbviewer jupyter org github anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading pairs trading and linear regression ipynb notebook introduction to linear regression and machine learning model building process https nbviewer jupyter org github anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading linear 20regression ipynb moving to backtesting statsmodel linear regression quantopian ide codes for pairs trading using linear regression model statsmodel pre 2008 https nbviewer jupyter org github anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading pairs 20trading 20statsmodels 20linear 20pre 202008 py and quantopian ide codes for pairs trading using linear regression model statsmodel post 2008 https nbviewer jupyter org github anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading pairs 20trading 20statsmodels 20linear 20post 202008 py this backtest utilise python statsmodel to build the linear regression model we then move on to illustrate how one can use the python scikit learn model to do likewise scikit learn linear regression quantopian ide codes for pairs trading using linear regression model scikit learn https nbviewer jupyter org github anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading pairs 20trading 20scikit learn 20linear py scikit learn lasso regression lasso regression https nbviewer jupyter org github anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading pairs 20trading 20 20lasso 20regression py scikit learn ridge regression ridge regression https nbviewer jupyter org github anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading pairs 20trading 20 20ridge 20regression py scikit learn bayesian ridge regression bayesian ridge regression https nbviewer jupyter org github anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading pairs 20trading 20 20bayesian 20ridge 20regression py scikit learn elasticnet regression elasticnet regression https nbviewer jupyter org github anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading pairs 20trading 20 20elastic 20net py 1 2 pairs trading and kalman filter pairs trading design with kalman filter https nbviewer jupyter org github anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading pairs trading with linear regression and kalman filter ipynb 1 3 trend following machine learning trend following strategies with machine learning https nbviewer jupyter org github anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading trend following strategies penalized regression approach ipynb 1 4 references ucl characterization of financial time series https github com anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading rn 11 01 pdf empirical properties of asset returns stylized facts and statistical issues rama cont https github com anthonyng2 machine learning for finance blob master regression 20based 20machine 20learning 20for 20algorithmic 20trading empirical 20properties 20of 20asset 20returns pdf 2 classification based machine learning for algorithmic trading this portion is under active development at the moment i have uploaded some of my codes and backtesting results a common use of classification ml is to predict the next day s result you can find some examples here https www quantstart com articles forecasting financial time series part 1 some of the ml classification methods were capable of achieving prediction accuracy of pver 60 does that translate directly to returns and out performance over simple buy and hold strategy check out the backtesting tearsheets for the answer classification based machine learning algorithm https nbviewer jupyter org github anthonyng2 machine learning for finance blob master classification 20based 20machine 20learning 20for 20algorithmic 20trading classification 20based 20machine 20learning 20algorithm ipynb | ai |
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Hands-On-Artificial-Intelligence-for-IoT | hands on artificial intelligence for iot a href https www packtpub com big data and business intelligence hands artificial intelligence iot utm source github utm medium repository utm campaign 9781788836067 img src https d1ldz4te4covpm cloudfront net sites default files imagecache ppv4 main book cover b09828 png alt book name height 256px align right a this is the code repository for hands on artificial intelligence for iot https www packtpub com big data and business intelligence hands artificial intelligence iot utm source github utm medium repository utm campaign 9781788836067 published by packt expert machine learning and deep learning techniques for developing smarter iot systems what is this book about there are many applications that use data science and analytics to gain insights from terabytes of data these apps however do not address the challenge of continually discovering patterns for iot data in hands on artificial intelligence for iot we cover various aspects of artificial intelligence ai and its implementation to make your iot solutions smarter this book covers the following exciting features apply different ai techniques including machine learning and deep learning using tensorflow and keras access and process data from various distributed sources perform supervised and unsupervised machine learning for iot data implement distributed processing of iot data over apache spark using the mllib and h2o ai platforms forecast time series data using deep learning methods if you feel this book is for you get your copy https www amazon com dp 1788836065 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 for example chapter02 the code will look like the following a tf placeholder tf float32 none name a b tf placeholder tf float32 none name b following is what you need for this book if you are a data science professional or a machine learning developer looking to build smart systems for iot hands on artificial intelligence for iot is for you if you want to learn how popular artificial intelligence ai techniques can be used in the internet of things domain this book will also be of benefit a basic understanding of machine learning concepts will be required to get the best out of this book with the following software and hardware list you can run all code files present in the book chapter 1 12 software and hardware list chapter software required os required 1 tensorflow1 x python 3 5 numpy 1 14 windows10 macos 10 x ubuntu 16 04 2 tensorflow1 x python 3 5 numpy 1 14 windows10 macos 10 x ubuntu 16 04 keras openpyxl sql hdfs h5py 3 5 7 9 11 tensorflow1 x python 3 5 numpy 1 14 windows10 macos 10 x ubuntu 16 04 keras scikit learn matplotlib pandas scipy 6 tensorflow1 x python 3 5 numpy 1 14 macos 10 x ubuntu 16 04 keras scikit learn matplotlib pandas open ai gym random 8 tensorflow1 x python 3 5 numpy 1 14 ubuntu 16 04 keras scikit learn matplotlib scipy pandas kafka tensorframes sparkdl pyspark tensorflowonspark we also provide a pdf file that has color images of the screenshots diagrams used in this book click here to download it http www packtpub com sites default files downloads 9781788836067 colorimages pdf related products other books you may enjoy artificial intelligence with python packt https www packtpub com big data and business intelligence artificial intelligence python utm source github utm medium repository utm campaign 9781786464392 amazon https www amazon com dp 178646439x artificial intelligence by example packt https www packtpub com big data and business intelligence artificial intelligence example utm source github utm medium repository utm campaign 9781788990547 amazon https www amazon com dp 1788990544 get to know the author amita kapoor is an associate professor in the department of electronics srcasw university of delhi and has been actively teaching neural networks and artificial intelligence for the last 20 years she completed her master s in electronics in 1996 and her phd in 2011 during her phd she was awarded the prestigious daad fellowship to pursue part of her research at the karlsruhe institute of technology karlsruhe germany she was awarded the best presentation award at the photonics 2008 international conference she is an active member of acm aaai ieee and inns she has co authored two books she has more than 40 publications in international journals and conferences her present research areas include machine learning artificial intelligence deep reinforcement learning and robotics other books by the author tensorflow 1 x deep learning cookbook https www packtpub com big data and business intelligence tensorflow 1x deep learning cookbook utm source github utm medium repository utm campaign 9781788293594 suggestions and feedback click here https docs google com forms d e 1faipqlsdy7datc6qmel81fiuuymz0wy9vh1jhkvpy57oimekgqib ow viewform if you have any feedback or suggestions 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 9781788836067 https packt link free ebook 9781788836067 a p | server |
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n8n-design-system | n8n design system a component system for n8n https n8n io using storybook to preview you can preview project here https n8n io github io n8n design system index html project setup npm install compiles and hot reloads for development npm run storybook build static pages npm run build storybook run your unit tests npm run test unit lints and fixes files npm run lint build css files npm run build theme monitor theme files and build any changes npm run watch theme | os |
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ADS-Matlab-Interface | ads matlab interface keysight advanced design system ads to matlab interface introduction this tadsinterface class allows for communication with keysight advanced design system ads from within matlab it has been developed and tested under windows platform but small modifications are expected to adapt it for linux warning the interface uses undocumented features of ads therefore there is a chance that it will stop working under a new release of ads the current version of the interface has been tested with ads 2016 1 2017 2019 and 2022 note also that the interface has been used for simulations using harmonic balance solver in ads it should work with other solvers as well but it is not guaranteed features this ads matlab interface allows set paths and environmental variables required by ads change parameters in the ads project s schematic var eqn component change parameters of components like snp capacitors etc run simulation read results from the dataset files generated by the solver which can be run either from matlab using this interface or natively from ads ide note that all parameter changes made by the interface affect only the project s netlist file and do not affect the schematic the netlist will be re generated by ads if simulation is started within its ide so the parameter changes here make sense only if the simulation is started by means of this interface demos documentation all functionalities are well documented in the included live script demos matlab r2018a or higher is desired in order to not loose code samples in the demos bugs feature requests if you encounter any errors notice some misfunction while using the interface or would like to have new functionality feel free to open an issue directly in github https github com korvin011 ads matlab interface issues however i cannot promise fast fix response due to lack of time for support acknowledgment i would like to thank jan simon for his great function getfullpath https se mathworks com matlabcentral fileexchange 28249 getfullpath it is very helpful for this interface | os |
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EmbeddedSystem | uva solar car team electrical team embedded system subgroup the embedded system sub group focuses on developing the embedded system for the solar car that controls the can bus driver interface and bps battery management system this repository contains all of the design files necessary to implement the electrical control systems necessary for the solar car project ecu the ecu is the primary controller for the majority of systems including motor control battery monitoring driver interface and mppt interface the pcb contains circuitry for interfacing buttons and switches on driver interface high current lights and horn as well as important not all pins are 12v or even 5v compatible certain pins connect directly to the teensy with no protection signal name of io signal in eeschema may or may not also be the net name voltage the voltages the pin is designed for direction the direction of the signal relative to the ecu description description of the signal user interface input control these pins are used for allowing the driver to command the vehicle all but the uart pins are 12v logic to reduce the number of pins required on the mcu we chose to wire 3 way position switches such that the end contacts connect to the rails and the center contact floats with a resistor divider to ensure the voltage is approximately vcc 2 when the switch is in the middle position signal pin voltage direction description brake ctrl 20 0 12v input brake potentiometer used to implement regen regen ctrl 17 0 12v input regen potentiometer used to set max regen percentage gearshift ctrl 14 0 12v input 3 way position switch 12v forward 6v neutral 0v reverse turnsig ctrl 15 0 12v input 3 way position switch 12v forward 6v neutral 0v reverse throttle ctrl 16 0 12v input throttle potentiometer the gas petal steer ctrl 21 a7 0 12v input potentiometer on steering wheel may be used for differential throttle control hazard ctrl 16 0 12v input pushbutton used to activate hazard lights toggles on changing edge horn ctrl 22 a6 0 12v input horn button down ctrl 26 0 12v input gui navigation pushbutton up ctrl 27 0 12v input gui navigation pushbutton sel ctrl 28 0 12v input gui navigation pushbutton kill sense 2 0 12v input used to detect if the power engaging the relays has been cut hazard led 25 0 12v output connected to hazard button led uart 1 rx 0 0 3 3v input used for nextion 3 2 lcd uart 1 tx 1 0 3 3v output used for nextion 3 2 lcd serial interface io these pins are used for communicating with various peripherals components and subsystems within the car can0 is reserved for the bms while can1 is used for all less critical systems uart pins are for future use signal pin voltage direction description can0 h 0 5v can high connected to can0 peripheral on teensy 3 6 through mcp2562 can0 l 0 5v can low connected to can0 peripheral on teensy 3 6 through mcp2562 can1 h 0 5v can high connected to can1 peripheral on teensy 3 6 through mcp2562 can1 l 0 5v can low connected to can1 peripheral on teensy 3 6 through mcp2562 uart 3 rx 7 0 3 3v input reserved for future use uart 3 tx 8 0 3 3v output reserved for future use uart 6 rx 47 0 3 3v input reserved for future use uart 6 tx 48 0 3 3v output reserved for future use lights and horn these pins are capable of high currents up to 5a distributed among the 4 outputs signal pin voltage direction description horn 57 0 12v output high power output for car horn can only source current headlights 42 0 12v output high power output for headlights can only source current brakelights 56 0 12v output high power output for brakelights can only source current strobe 6 0 12v output high power output for strobelight can only source current right blinkers 41 0 12v output high power output for right blinkers can only source current left blinkers 40 0 12v output high power output for left blinkers can only source current horn ctrl 22 0 12v input high power input for horn headlight ctrl 23 0 12v input high power input for headlights brake ctrl 20 0 12v input analog input for brakes used for regen motor control the motor can be interfaced via uart can and gpio as of now we do not have any api or knowledge of how to interface the motor over uart as it is not documented however it is possible to decompile the android app and reverse engineer whatever the app implements for now we are using can to retrieve important parameters from the motor such as voltage current rpm throttle and error codes the motor only outputs messages over can and does not interpret them the table below holds true for both motor r and motor l signals note all node names in the table below are preceded with motor r and motor l signal pin l pin r voltage direction description regen en 50 53 0 12v output enables regenerative braking on motor controller regen 36 pwm 37 pwm 0 5v output analog output sets regen level when throttle is disabled throttle 35 pwm 38 pwm 0 5v output sets throttle when fwd en or rev en are enabled eco en 49 39 0 12v output reduces maximum power of motor controller meter a11 a10 0 12v input analog output from motor controller fwd en 55 52 0 12v output forward enable rev en 54 51 0 12v output reverse enable software at the moment we have bits and pieces of code written but no unified project as of yet the can repository contains experemantal code for interfacing the can peripherals on the teensy as well as development towards a motor driver the completed motor driver will eventually be refactored into this repo | teensy36 teensy teensyduino can | os |
LM_PersonalInfoLeak | language model memorization vs association the code and data for are large pre trained language models leaking your personal information https arxiv org abs 2205 12628 findings of emnlp 22 introduction are large pre trained language models leaking your personal information we analyze whether pre trained language models plms are prone to leaking personal information specifically we query plms for email addresses with contexts of the email address or prompts containing the owner s name we find that plms do leak personal information due to memorization however since the models are weak at association the risk of specific personal information being extracted by attackers is low how does gpt 3 answer this question img width 1559 alt image src https user images githubusercontent com 47152740 198936706 cedccbb5 2b1c 415e 988c 7bffbb343686 png requirements see requirements txt run python pred py after this step the models predictions are stored as pkl files in results to analyze the results in csv files and get the scores python analysis py note the scripts test the 0 shot setting by default please edit the scripts i e settings for evaluation on other settings data data are available at data context pkl refers to the context setting k shot non domain pkl refers to the setting when domain is unknown k shot pkl refers to the setting when domain is known email2name pkl stores the mapping from email address to name name2email pkl stores the mapping from name to email address email freq pkl stores the frequency of email address citation the details of this repo are described in the following paper if you find this repo useful please kindly cite it inproceedings huang2022large title are large pre trained language models leaking your personal information author huang jie and shao hanyin and chang kevin chen chuan booktitle findings of the association for computational linguistics emnlp 2022 year 2022 | association email-address language-model memorization personal-privacy pretrained-language-model privacy privacy-attacks enron-emails | ai |
SimpleDNN | simplednn maven central https img shields io maven central v com kotlinnlp simplednn svg label maven 20central https search maven org search q g 22com kotlinnlp 22 20and 20a 22simplednn 22 build status https travis ci org kotlinnlp simplednn svg branch master https travis ci org kotlinnlp simplednn simplednn is a machine learning lightweight open source library written in kotlin whose purpose is to support the development of feed forward https en wikipedia org wiki feedforward neural network feedforward neural network and recurrent https en wikipedia org wiki recurrent neural network recurrent neural network artificial neural networks simplednn is part of kotlinnlp http kotlinnlp com kotlinnlp and has been designed to support relevant neural network architectures in natural language processing tasks such as pos tagging syntactic parsing and named entity recognition as it is written in kotlin it is interoperable with other jvm languages e g java and scala mathematical operations within the library are performed with jblas https github com mikiobraun jblas jblas different libraries can be used instead although during our experiments it proved to be the fastest the effort required is minimum as the essential mathematical functions are wrapped in a single package and fully tested saving you valuable time note simplednn does not use the computational graph model and does not perform automatic differentiation of functions in case you are looking for state of the art technology to create sophisticated flexible network architectures you should consider the following libraries pytorch https github com pytorch pytorch pytorch dynet https github com clab dynet dynet keras https github com fchollet keras keras tensorflow https github com tensorflow tensorflow tensorflow and deeplearning4j https github com deeplearning4j deeplearning4j deeplearning4j if instead a simpler yet well structured neural network almost ready to use is what you need then you are in the right place introduction building a basic neural network with simplednn does not require much more effort than just configuring a stack of layers with one input layer any number of hidden layers and one output layer kotlin create a fully connected neural network with an input layer with dropout two hidden layers with elu activation function and an output one with softmax activation for classification purpose val network stackedlayersparameters layerinterface input layer size 784 dropout 0 25 layerinterface first hidden layer size 100 activationfunction elu connectiontype layertype connection feedforward layerinterface second hidden layer size 100 ctivationfunction elu connectiontype layertype connection feedforward layerinterface output layer size 10 activationfunction softmax connectiontype layertype connection feedforward getting started import with maven xml dependency groupid com kotlinnlp groupid artifactid simplednn artifactid version 0 14 0 version dependency examples try some examples of usage of simplednn running the files in the examples folder to make the examples working download the datasets here https www dropbox com sh ey4vmajm54xf06v aadn8nx90wguoxuzeuy6tbtba dl 0 simplednn examples datasets then set their paths copying the file example config configuration yml example to example config configuration yml and editing it properly license this software is released under the terms of the mozilla public license v 2 0 https mozilla org mpl 2 0 mozilla public license v 2 0 contributions we greatly appreciate any bug reports and contributions which can be made by filing an issue or making a pull request through the github page https github com kotlinnlp simplednn simplednn on github | neural-network kotlin machine-learning recurrent-neural-networks feedforward-neural-network attention-mechanism natural-language-processing artificial-intelligence | ai |
dig4639-mobile-dev | mobile development this repository contains work completed during spring 2020 in dr murray s dig4639 mobile development class simple this is a sample change on the local repository structure the ice folder contains in class exercises about me https www linkedin com in kyle melendez 8368a2123 my preffered job is something involving front end mostly html css and javascript this should be replaced this is the change npm | front_end |
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EmbeddedSystemNJU2018-Demo | embeddedsystemnju2017 demo demo and designated library file for software design of the coursework to be assigned on introduction to embedded systems in the first semester of year 2017 2018 software institute nanjing university contents basic principles of code of the static library header file to be included in order to utilize the library a static library file provided in releases section demos to demonstrate usage demos to use opencv dependencies hardware raspberrypi raspberrypi 3 model b is provided when using raspberry pi 2 maybe you need an extra wireless usb nic device driver circuit for powering dc motors dc motors and steering engine the former is for motion and the latter is for turning independent power supply for motors raspberry pi and motors shouldn t be powered by the same battery this may interfere with the stability of raspberry pi software linux running on raspberry pi raspbian and ubuntu recommended opencv wiringpi usually integrated with raspbian installation manuals can be found on the websites of raspberry pi and opencv rules and restrictions these documents are visible on cms and or wiki pages of this repository violation shall receive appropriate punishment on gradings the library is open source but using codes directly in the contest is forbidden the library is released under the mit liccense help and assistance according to the rule of competition there is no assistance in practical coding if you consider bugs about this library please test on those demos first the library is considered bug free only if any of those demos fails to run malfunctions are usually caused by hardware wearing down of wirings or parts you can call the stuff to repair the hardware part thanks this demo related to opencv refers to a work of jdorweiler the original links are listed below https github com jdorweiler lane detection the original repository has no licenses so i relicense my works under mit license | os |
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gobarber-web | h1 align center img alt gobarber web src https res cloudinary com lukemorales image upload v1564533051 readme logos gobarber hg5ddx png br gobarber web h1 h4 align center a barber scheduling app that shows to the barber his agenda for the day h4 p align center img alt github top language src https img shields io github languages top lukemorales gobarber api svg img alt github language count src https img shields io github languages count lukemorales gobarber api svg a href https www codacy com app lukemorales gobarber api utm source github com amp utm medium referral amp utm content lukemorales gobarber api amp utm campaign badge grade img alt codacy grade src https api codacy com project badge grade 1ca82febe92a47e4a9a03d6621617cc0 a img alt repository size src https img shields io github repo size lukemorales gobarber api svg a href https github com lukemorales gobarber api commits master img alt github last commit src https img shields io github last commit lukemorales gobarber api svg a a href https github com lukemorales gobarber api issues img alt repository issues src https img shields io github issues lukemorales gobarber api svg a img alt github src https img shields io github license lukemorales gobarber api svg p p align center a href rocket technologies technologies a nbsp nbsp nbsp nbsp nbsp nbsp a href information source how to use how to use a nbsp nbsp nbsp nbsp nbsp nbsp a href memo license license a p app screenshot https res cloudinary com lukemorales image upload v1564536567 readme logos login pj8pih jpg app screenshot https res cloudinary com lukemorales image upload v1564536567 readme logos schedules tgpmie jpg app screenshot https res cloudinary com lukemorales image upload v1564536567 readme logos profile nl7oco jpg app screenshot https res cloudinary com lukemorales image upload v1564536567 readme logos signup xwdwqm jpg rocket technologies this project was developed at the rocketseat gostack bootcamp https rocketseat com br bootcamp with the following technologies reactjs https reactjs org create react app configuration override https github com sharegate craco redux https redux js org redux saga https redux saga js org react router v4 https github com reacttraining react router styled components https www styled components com axios https github com axios axios history https www npmjs com package history immer https github com immerjs immer polished https polished js org react toastify https fkhadra github io react toastify react icons http react icons github io react icons react perfect scrollbar https github com opuscapita react perfect scrollbar unform https github com rocketseat unform yup https www npmjs com package yup date fns https date fns org reactotron https infinite red reactotron vs code vc with editorconfig vceditconfig and eslint vceslint information source how to use to clone and run this application you ll need git https git scm com node js v10 16 nodejs or higher yarn v1 13 yarn or higher installed on your computer and the gobarber api https github com lukemorales gobarber api from your command line bash clone this repository git clone https github com lukemorales gobarber web go into the repository cd gobarber web install dependencies yarn install run the app yarn start memo license this project is under the mit license see the license https github com lukemorales gobarber api blob master license for more information made with by luke morales wave get in touch https www linkedin com in lukemorales nodejs https nodejs org yarn https yarnpkg com vc https code visualstudio com vceditconfig https marketplace visualstudio com items itemname editorconfig editorconfig vceslint https marketplace visualstudio com items itemname dbaeumer vscode eslint | front_end |
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MApp-Website | mapp website logo http spencer shadley github io img portfolio mapp jpg about website i built over the 2014 2015 winter break to teach students how to build android applications based off of content i created when developing a similar course for the garland independent school district stats as of 1 14 16 within one day 1 500 pages were viewed within three days 10 000 pages were viewed currently there are 100 000 pages viewed people from 150 countries have taken the course no advertisements all word of mouth links website http mapp develop appspot com supplemental android application https play google com store apps details id com feztheforeigner mobileapps | front_end |
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subgraphs | messari standard subgraphs bull github license https img shields io badge license mit blue https github com messari subgraphs blob master license prs welcome https img shields io badge prs welcome brightgreen svg docs contributing md issues report https img shields io badge issues report yellow svg https github com messari subgraphs issues new p align center a href https messari io protocol explorer all protocols img src docs images messari logo png alt messari logo width 460 a p messari subgraphs set an industry leading standard for on chain data utilizing the graph https thegraph com these subgraphs extract raw blockchain data and transform it into meaningful metrics for products and analytics we aim to make sense of defi protocols in an open holistic approach capturing every piece of data from a given protocol type protocol types supported lending schema lending graphql cdp schema lending graphql dex schema dex amm graphql yield aggregator schema yield graphql nft marketplace schema nft marketplace graphql network schema network graphql bridge schema bridge graphql perpetual futures schema derivatives perpfutures graphql options schema derivatives options graphql governance sub if you are a protocol and want to collaborate please visit messari io web3 data collaboration https messari io web3 data collaboration sub working environment go to docs setup md docs setup md to learn how to setup your machine for messari subgraph development learn the project it is important to familiarize yourself with the project structure and tooling to build efficiently go to docs structure md docs structure md and docs tooling md docs tooling md to learn more familiarize yourself with our schemas labeled schema protocol type graphql read more details in docs schema md docs schema md we update our schemas as necessary you can find out about each upgrade in docs changes md docs changes md to learn about messari standard methodologies see docs methodology md docs methodology md becoming a subgraph developer becoming a good subgraph developer will take patience and practice the following resources are for developers of all skill levels to learn the ins and outs of subgraph development for a full walkthrough of our subgraph development process visit docs walkthrough md docs walkthrough md resources for development of varying levels can be found in docs resources md docs resources md to learn about common errors best error handling practices and debugging see docs errors md docs errors md subgraph performance is also a concern learn about indexing querying performance by reading docs performance docs performance md learn about retrieving prices in subgraphs and how to handle this in docs oracles md docs oracles md contributing guidelines we welcome contributions from the community you can point out or fix bugs suggest changes add new features or add new subgraphs for bugs features or change requests please submit an issue https github com messari subgraphs issues following our guide docs issues md general contribution guidelines and practices will be found in docs contributing md docs contributing md development status you can find a visualizer with the status of all messari subgraphs at subgraphs xyz https subgraphs messari io the code lives under dashboard you can see our subgraphs supporting the data for our product protocol metrics https messari io protocol explorer all protocols quick note the raw deployment status of all subgraphs lives in deployment deployment json deployment deployment json | graphql thegraph defi solidity ethereum blockchain | blockchain |
ny_taxi_rides_zoomcamp | welcome to your new dbt project how to run this project about the project this project is based in dbt starter project https github com dbt labs dbt starter project generated by running dbt init try running the following commands dbt run dbt test a project includes the following files dbt project yml file used to configure the dbt project if you are using dbt locally make sure the profile here matches the one setup during installation in dbt profiles yml yml files under folders models data macros documentation files csv files in the data folder these will be our sources files described above files inside folder models the sql files contain the scripts to run our models this will cover staging core and a datamarts models at the end these models will follow this structure image https user images githubusercontent com 4315804 152691312 e71b56a4 53ff 4884 859c c9090dbd0db8 png workflow image https user images githubusercontent com 4315804 148699280 964c4e0b e685 4c0f a266 4f3e097156c9 png execution after having installed the required tools and cloning this repo execute the following commnads 1 change into the project s directory from the command line cd taxi rides ny 2 load the csvs into the database this materializes the csvs as tables in your target schema dbt seed 3 run the models dbt run 4 test your data dbt test alternative use dbt build to execute with one command the 3 steps above together 5 generate documentation for the project dbt docs generate 6 view the documentation for the project this step should open the documentation page on a webserver but it can also be accessed from http localhost 8080 dbt docs serve dbt resources learn more about dbt in the docs https docs getdbt com docs introduction check out discourse https discourse getdbt com for commonly asked questions and answers join the chat http slack getdbt com on slack for live discussions and support find dbt events https events getdbt com near you check out the blog https blog getdbt com for the latest news on dbt s development and best practices | cloud |
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TypeScriptFullStackShell | typescriptfullstackshell setting up a web application for full stack typescript development commands npm start start the app in production mode production code must be built for production first npm run build npm run start dev start the express server in dev mode will activate typescript file watcher and generate source maps npm run build at root will build the app for production contents are output to build npm test run back end unit tests if you want to run a specific unit test run npm run test path to the unit test file i e npm test controllers demo democontroller because source map files are generated for map files too debugging in ides should still work links a href https github com seanpmaxwell overnight overnightjs a | front_end |
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COEN-20-21 | coen 20 21 these are bits of code from my embedded systems coen 20 and logic design coen 21 | os |
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atomify | atomify build status https travis ci org atomify atomify svg https travis ci org atomify atomify gitter https badges gitter im join chat svg https gitter im atomify atomify utm source badge utm medium badge utm campaign pr badge utm content badge dependencies up to date https david dm org atomify atomify png https david dm org atomify atomify atomic web development combining the power of npm browserify rework and more to build small fully encapsulated client side modules description atomify provides a centralized point of access to atomify js http github com atomify atomify js and atomify css http github com atomify atomify css both in code and on the command line it also offers a server with live reload and on the fly bundling support to make development a breeze examples you can learn from examples in this repository https github com atomify atomify examples api atomify opts cb just like its constituent pieces atomify is a function that takes an opts object and a callback function opts opts js options to be passed to atomify js https github com atomify atomify js opts opts css options to be passed to atomify css https github com atomify atomify css opts opts assets used to configure opts js assets and opts css assets simultaneously and identically see links above opts server options to be passed to the development server callback just like the callbacks used by atomify js and atomify css but with a third parameter to denote the type of bundle being provided cb err src type where type is either js or css api example js build js var atomify require atomify var jsconfig entry js shorthand for entry entry js var cssconfig entry entry css variables background f00 function cb err src type if type js do something with js source bundle else do something with css source bundle atomify js jsconfig css cssconfig cb if you don t need to access the bundled source simply provide a file path as the output property in your options and atomify will write the file for you atomify js and atomify css as a convenience you can access atomify js and atomify css via properties on the atomify function js var atomify require atomify atomify js require atomify js atomify css require atomify css development server atomify includes a development server that provides things like on the fly bundling and live reload browser sync support to make your workflow lightning fast atomify server opts provides basically the same api as atomify itself with a few extra options documented below added in the biggest difference of course is that instead of writing to a file or calling a callback function atomify server responds to http requests the server can also be configured by including a server property in the opts object when calling atomify opts just like with atomify the options passed to atomify server are expected to have a js and or css field when the entry option of either of these is requested the server will return the results of bundling your code if you don t want to include the actual path to your entry file in your html you can also provide an alias option field when the alias path is requested the server will bundle using your entry path opts server you can provide server specific options in this field opts server port port to listen on default 1337 opts server open if provided open the url in your default browser opts server path the path to open appended to http localhost port by default default default which is a generated html file that includes your css and js bundles automatically opts server url full url to open instead of http localhost port path opts server hostname use your machine s local hostname via node s os hostname instead of localhost ideal for accessing pages from mobile devices on the same lan aliased as h opts server lr enables live reload support by injecting the live reload script into any html pages served supports the following sub properties sync use browsersync aliased as s if provided as an object will be used as the ghostmode https github com shakyshane browser sync wiki options ghostmode option for browsersync port port for browsersync server to run on default 3000 patterns globbing patterns to pass to browsersync https www npmjs org package browser sync for watching default html relative to process cwd as well as all files in the dependency graph of your js and css bundles quiet suppress file change notifications on the command line default false verbose log browsersync s debuginfo to the console default false opts server sync shortcut for specifying opts server lr as sync true aliased as s opts server st options to pass to st https www npmjs org package st static file server which is what serves all non entry alias requests opts server html override the default html served at default pass either a filepath or a function if you pass a function you ll be passed one options argument with the urls to the bundled js and css you should insert those into your html and return a string js server html function html paths done it s important to include the body tags so that the livereload snippet from browsersync can be inserted var html body link rel stylesheet href paths css h1 your current url paths request h1 script src paths js script body you can return an error if something went wrong done null html if you pass a filepath the bundled js and css will automatically be inserted at the bottom of your file however you can place the strings atomify css and atomify js when you want the relevant paths inserted to override this behavior opts server spamode when set to true the default html will always be served this is useful for single page apps that have a router package json config in order to support atomify turtles all the way down you can also specify your configuration in package json simply recreate an opts object structure in json with atomify as the key omit output properties if not a top level package json atomify server lr true js entry index js output dist bundle js css entry index css plugins rework plugin inline src assets rework default unit output example bundle css for detailed information on configuring rework plugins in package json see the relevant section https github com atomify atomify css packagejson config of the atomify css readme cli thanks to subarg https github com substack subarg nearly everything you can do in code or json you can do on the command line js options can be specified in a js j subarg context and css options can be specified in a css c subarg context server options can be specified in a server s subarg context if you supply the debug d or output o args outside the js and css contexts they will apply to both js and css bundles when providing an output argument that applies to both omit the file extension and it will be applied correctly for you you can also configure aliases by appending them after a in your entry field like j entry js bundle js get a complete listing of options by running atomify help cli examples bash atomify j entry js bundle js atomify j e entry js e other js o bundle js d w atomify j entry js t funkify c entry css o bundle atomify j src entry js bundle js c styles entry css bundle css server open any top level args js css server passed on the command line will override the corresponding configuration defined in package json non conflicting top level items will be merged with package json configuration install bash npm install atomify | front_end |
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OpenBazaar-Client | note this project is no longer maintained please see version 2 at https github com openbazaar openbazaar desktop openbazaar client v1 0 deprecated build status https travis ci org openbazaar openbazaar client svg https travis ci org openbazaar openbazaar client slack status http slack openbazaar org badge svg https openbazaar slackin drwasho herokuapp com you must be running the openbazaar backend https github com openbazaar openbazaar server for the client to work if you are using a remote server a server on a different computer your connection will fail on the first install and you will need to enter the information for the remote server as a new connection dependencies nodejs https nodejs org en download v6 x install via package manager https nodejs org en download package manager ensure that npm is added to your path running 1 clone the client repository into a directory of your choice git clone https github com openbazaar openbazaar client git 2 navigate into the new folder created in 1 cd openbazaar client 3 install the client npm install 4 run the client npm start remember you must be running the openbazaar server https github com openbazaar openbazaar server for the client to function properly if you want to access the test network testnet run the server using the t flag e g python openbazaard py start t if your router blocks your port after starting and stopping the server you can set your server to a new port with the p flag p followed by a port number if the server component has not generated a guid which happens only once when the server is first started then the client will not fully start up until the guid is created current v1 mainnet release tracker can be found here 965 https github com openbazaar openbazaar client issues 965 api documentation the client uses the following rest api calls get calls https gist github com drwasho 742505589f62f6aa98b4 post calls https gist github com drwasho bd4b28a5a07c5a952e2f websocket api calls are yet to be documented translations translators around the world are welcomed you can start translating at our transifex project https www transifex com ob1 openbazaar many thanks | javascript nodejs electron openbazaar p2p | front_end |
Grants-Program | web3 foundation grants program omit in toc p align center img src static img grants program png style width 1300px p wave introduction wave introduction guidelines guidelines project ideas project ideas support support team team level slider levels level slider levels pencil process pencil process 1 application 1 application 2 application review 2 application review 3 milestone delivery and payment 3 milestone delivery and payment changes to a grant after approval changes to a grant after approval mailbox with mail suggest a project mailbox with mail suggest a project hammer and wrench maintenance grants hammer and wrench maintenance grants moneybag referral program moneybag referral program bulb help bulb help real time conversation real time conversation office hours office hours additional information additional information rocket alternative funding sources rocket alternative funding sources substrate builders program vs treasury vs web3 grants substrate builders program vs treasury vs web3 grants substrate builders program substrate builders program treasury treasury hackathons hackathons other grant or bounty programs other grant or bounty programs wave introduction as part of our commitment to promoting the web3 ecosystem we offer a comprehensive grants program focused on funding software development and research efforts related to polkadot and kusama for more information about the web3 foundation please visit the about page https web3 foundation about on our website guidelines anyone is welcome to apply for a grant projects funded through our programs are broad in scope but our focus lies on strong technical projects that add value to the ecosystem generally your project will have better chances to be accepted if it presents a well researched or tested concept for which ideally you are able to show some prior work you can demonstrate that the project will be maintained after completion of the grant be it through an obvious commitment to the technology from your side additional funding sources or an existing business model your team has proven experience with the relevant languages and technologies and or a strong technical background you will be asked to provide the github profiles of your team members as part of your application which we will examine for past activity and code quality naturally you can also link to projects on other platforms your application is rich in technical details and well defined you can clearly present how your project stands out among competitors or implements technology that doesn t exist in the ecosystem yet additionally it must fulfill the following requirements all code produced as part of a grant must be open sourced and it must also not rely on closed source software for full functionality we prefer apache 2 0 but gplv3 mit or unlicense are also acceptable we do not award grants for projects that have been the object of a successful token sale applications must not mention a specific token furthermore the focus of the application should lie on the software that is being implemented research being carried out as part of the grant and less on your project venture operation for the purpose of the application and delivery think about how others might also benefit from your work as a general rule teams are asked to finish a grant before applying for another one lastly we do not fund projects that actively encourage gambling illicit trade money laundering or criminal activities in general in addition to the information provided on your application note that your project will need to comply with our guidelines for milestone deliverables https github com w3f grants program blob master docs support 20docs milestone deliverables guidelines md in particular we require all projects to create documentation that explains how their project works at a minimum written documentation is required for funding tutorials or videos are also helpful for new users to understand how to use your product please also heed our announcement guidelines https github com w3f grants program blob master docs support 20docs announcement guidelines md for grant related communications finally we take licensing and the right of all teams in and outside the ecosystem to be recognised for their work very seriously using others work with no attribution or indication that this was not your own work as part of a milestone delivery will lead to immediate termination please reach out to us before submitting if you have any doubts on how to comply with a specific license and we ll be happy to help we also try to enforce our code of conduct code of conduct md and based on this may block users https github blog 2016 04 04 organizations can now block abusive users project ideas an overview of existing projects in the web 3 0 technology stack along with broad project ideas we would potentially be interested in funding can be found here https wiki polkadot network docs build open source as well as a list of previously accepted applications here https github com w3f grants program blob master applications index md requests for proposals https github com w3f grants program blob master docs rfps md rfps represent concrete ideas for projects that we would like to see implemented several teams may apply for the same rfp so even if another team has already applied to implement a certain rfp we invite you to do the same if you re interested finally you don t need to start your own project in order to be eligible for a grant instead some teams choose to port existing work to substrate where the pertinent licenses allow or even to contribute to an existing open source project in the latter case you should check in advance that the maintainers of the project are interested in your contribution and the acceptance of the milestones will generally be tied to the inclusion of your work in said project see the maintenance grants section hammer and wrench maintenance grants for more info if you have a good concept of the technical challenges that your idea entails and would like feedback input before submitting it you can send us an email mailto grants web3 foundation and tell us about it support the scope of our grants programs consists of funding and feedback on delivered milestones this means that we do not provide hands on support as part of a grant but if you face specific issues during development we will do our best and try to direct you to the correct resources if this sounds like something you would like however you may also want to apply to parity s substrate builders program https www substrate io builders program which provides hands on technical ecosystem and strategical long term support and access to extensive resources you can find general documentation and more information on substrate on the substrate developer hub https substrate dev and we encourage you to join the community https substrate dev en community in order to get help with specific issues or to stay up to date with the most recent developments for questions about the grants program itself see our faq docs faq md frequently asked questions team w3f grants committee omit in toc the committee consists of individuals who know the funding priorities of the polkadot ecosystem and is responsible for evaluating grant applications and providing feedback on these in cases where a niche expert opinion is desirable one of the committee members may request such a review santiago balaguer https github com sbalaguer aeron buchanan https github com aeronbuchanan gautam dhameja https github com gautamdhameja david hawig https github com noc2 diogo mendon a https github com dsm w3f sebastian m ller https github com semuelle bill laboon https github com laboon keegan quigley https github com keeganquigley nikhil ranjan https github com nikw3f raul romanutti https github com rrtti seraya takahashi https github com takahser benjamin wei https github com benwhitejam gavin wood https github com gavofyork w3f grants evaluators omit in toc evaluators are individuals able to evaluate the technology delivered as a result of the grants program the committee has the right to add or remove evaluators on the basis of supermajority david hawig https github com noc2 diogo mendon a https github com dsm w3f sebastian m ller https github com semuelle keegan quigley https github com keeganquigley nikhil ranjan https github com nikw3f seraya takahashi https github com takahser w3f operations team omit in toc the operations team takes care of legal documents invoicing and remittances melanie diener https github com meldien federica dubbini https github com fededubbi rouven p rez https github com rouvenp level slider levels the w3f grants program offers different grant levels to help you best depending on your current stage hatching chick level 1 instagrants omit in toc target individuals small teams amount up to 10 000 requirements 2 approvals benefits feedback during application process and evaluation introduction to related teams projects baby chick level 2 omit in toc target small teams start ups amount up to 30 000 requirements 3 approvals benefits all of the above co promotion https github com w3f grants program blob master docs support 20docs announcement guidelines md grants program badge https github com w3f grants program blob master docs support 20docs grant badge guidelines md fast track to substrate builders program https www substrate io builders program rooster level 3 omit in toc target companies foundations with a proven track record amount unlimited requirements 5 approvals for 100k web3 foundation council approval pitch call benefits all of the above vc introductions pencil process loudspeaker payments can be made in usdt and usdc on the polkadot assethub https wiki polkadot network docs learn assets bitcoin and fiat usd eur chf please indicate your preference in the application as outlined in our application template https github com w3f grants program blob master applications application template md plain 1 l7 if you want to apply in private you can do so arrow right here https docs google com forms d e 1faipqlsfmfjirmdqdrk 4ohnasm6bakii7rz b1jwtbcpkuh6n7m2ww viewform note that this is generally a slower process and imposes stricter requirements on applicants 1 application 0 please read our faqs https github com w3f grants program blob master docs faq md category guidelines https github com w3f grants program blob master docs support 20docs grant guidelines per category md announcement guidelines https github com w3f grants program blob master docs support 20docs announcement guidelines md and terms conditions https github com w3f grants program blob master docs support 20docs t 26cs md to familiarize yourself with the subtleties of grants applications and the program as a whole 1 fork https github com w3f grants program fork this repository 2 in the newly created fork create a copy of the application template applications application template md applications application template md if you re using the github web interface you will need to create a new file and copy the contents https raw githubusercontent com w3f grants program master applications application template md of the template inside the new one make sure you do not modify the template file directly in the case of a maintenance application use the maintenance template maintenance template applications maintenance maintenance template md instead in the case of a research application use the research template research template applications application template research md instead 3 name the new file after your project project name md 4 fill out the template with the details of your project the more information you provide the faster the review please refer to our grant guidelines for most popular grant categories https github com w3f grants program blob master docs support 20docs grant guidelines per category md and make sure your deliverables present a similar same level of detail to get an idea of what a strong application looks like you can have a look at the following examples 1 https github com w3f grants program blob master applications project aurras mvp phase 1 md 2 https github com w3f grants program blob master applications project bodhi md 3 https github com w3f grants program blob master applications pontem md 4 https github com w3f grants program blob master applications spartan poc consensus module md naturally if you re only applying for a smaller grant that only consists of say ui work you don t need to provide as much detail 5 once you re done create a pull request in our main grants program repository https github com w3f grants program the pull request should only contain one new file the markdown file you created from the template 6 you will see a comment template that contains a checklist you can leave it as is and tick the checkboxes once the pull request has been created please read through these items and check all of them 7 sign off on the terms and conditions https github com w3f grants program blob master docs support 20docs t 26cs md presented by the cla assistant https github com claassistantio bot as a contributor license agreement you might need to reload the pull request to see its comment 2 application review 1 the committee w3f grants committee can and usually does issue comments and request changes on the pull request 2 clarifications and amendments made in the comments need to be included in the application you may address feedback by directly modifying your application and leaving a comment once you re done generally if you don t reply within 2 weeks the application will be closed due to inactivity but you re always free to reopen it as long as it hasn t been rejected 3 when all requested changes are addressed and the terms and conditions have been signed someone will mark your application as ready for review and share it internally with the rest of the committee 4 the application will be accepted and merged as soon as it receives the required number of approvals see levels level slider levels or closed after two weeks of inactivity unless specified otherwise the day on which it is accepted will be considered the starting date of the project and will be used to estimate delivery dates 3 milestone delivery and payment milestones are to be delivered on the grant milestone delivery https github com w3f grant milestone delivery repository following the process https github com w3f grant milestone delivery mailbox milestone delivery process described therein changes to a grant after approval accepted grant applications can be amended at any time however this necessitates a reevaluation by the committee and the same number of approvals as an application according to the levels level slider levels if your application has been accepted and during development you find that your project significantly deviates from the original specification please open a new pull request that modifies the existing application this also applies in case of significant delays if your delivery schedule significantly changes please also open a pull request with an updated timeline if your deliveries are significantly delayed and we cannot get a hold of you we will terminate the grant 3 approvals required regardless of level if a member of the committee creates the termination pr only two more approvals are required mailbox with mail suggest a project if you think that we should support the development of certain tools or projects that aren t in the polkadot kusama tech stack https wiki polkadot network docs build open source feel free to submit a suggestion using the process described below we are particularly interested in supporting projects that could be leveraged by other builders in our ecosystem submit an idea if you have an idea for a project or would like to highlight an area in which you d like to see teams build but lack the technical background to create a detailed outline you re welcome to open an issue https github com w3f grants program issues new or add it to the tech stack https wiki polkadot network docs build open source as a potentially interesting project we will review your suggestion and if necessary will create an rfp based on it and reach out to teams able to build it submit an rfp request for proposals ideas generally have better chances of being implemented if they re presented in a project outline format that can be picked up straight away by a team so if you have a good concept of the milestones required to bring your project to life you can follow the process below and directly submit an rfp 1 fork https github com w3f grants program fork this repository 2 in the newly created fork create a copy of the suggestion template rfps suggestion template md https github com w3f grants program blob master docs rfps suggestion template md inside the rfps https github com w3f grants program tree master docs rfps folder make sure you create a new file and copy the contents https raw githubusercontent com w3f grants program master docs rfps suggestion template md of the template into the new one and do not modify the template file directly 3 name the file after your idea project name md 4 fill out the template with the project details please include as many details as possible 5 once you re done create a pull request in our main grants program repository https github com w3f grants program blob master readme md the pull request should only contain one new file the markdown file you created from the template 6 you will see the same template as for creating an application please replace it with this one github pull request template rfp pr template md 7 the rfp will be accepted and merged as soon as it receives three approvals from w3f grants committee https github com w3f grants program w3f grants committee members hammer and wrench maintenance grants maintenance grants are yet another idea to get involved with the polkadot community if you are a user of an open source library that has gone out of date or you simply want to work on small new features fix bugs in these repos we can support your contributions via a grant we are happy to award rolling grants on a monthly basis as long as the work done within each time period is performed to a quality standard deemed satisfactory by the grant evaluators the process of applying for a maintenance grant is similar to what was already outlined above but instead of defining very detailed deliverables for each milestone upfront we will ask you to specify where possible the repo s that need maintenance outline of why the specific project should continue being supported broad overview of the features bugs that need development contributions an assurance that the current project owners are willing to review accept your contributions a note here if you re fully taking over the project it would make more sense for the current owners to transfer the repository to your organisation if you can t get in touch with them you may of course work on a fork max budget per month then at the end of each month you will need to provide a comprehensive report of the work done including the list of issues bugs pull requests worked on time spent on each of these finally the associated cost it is quite likely that the time allocation cost will vary from month to month depending on the nature of the project you re contributing to the delivery process and format should follow that of a typical milestone delivery https github com w3f grant milestone delivery mailbox milestone delivery process as will the processing of the payment please note that maintenance grants as the name suggests are meant to allow teams individuals to maintain a certain project and not to continue its development or implement larger features please use the traditional application process for this purpose the 1 month timeframe is just a guideline if you find it unsuitable for you or the chosen project for any reason feel free to adjust as seen fit and point this out in your application please bear in mind that the grants committee might be stricter in accepting maintainers when compared to typical grants mostly selecting for applicants with proven experience in the relevant tech stacks maintenance grants are only awarded for fixed timeframes the requested duration needs to be specified in the application moneybag referral program we give away 500 usd to each referral of a successful grant application by anyone having previously worked on a web3 foundation grant or a polkadot ambassador https wiki polkadot network docs ambassadors web3 foundation and parity employees do not qualify for the program even if they previously worked on a grant in order to be eligible for the referral bonus the application itself must contain the name of the polkadot ambassador https wiki polkadot network docs ambassadors or the github account of the grantee as well as the payment address for the referral bonus see the application template applications application template md payment is made in bitcoin or usdt usdc on polkadot assethub after delivery and approval of the first milestone bulb help real time conversation we have a matrix channel for grant related questions and activities head over there to ask grants related questions share your experience with other applications and grantees or simply hang out w3f grants community https matrix to xpynpdluswuwfdpaqr matrix org via web3 foundation via matrix org we also have matrix element channels for real time discussions on web3 and polkadot join the conversation web3 foundation chat https matrix to w3f matrix org polkadot space https matrix to polkadot web3 foundation kusama space https matrix to kusama web3 foundation office hours web3 foundation grants office hours are a chance to ask the grants team questions regarding a specific potential grant application it offers general guidance regarding the grants program some quick initial feedback and help how to navigate the ecosystem apply for office hours if you need feedback before submitting an application want to find out what kind of support there might be available or need help finding the resources you need it is not a chance to pitch your project especially since only a small subset of the committee will participate in the call to apply please fill out the office hours alarm clock form https forms gle 54xkiqu37wwdn9ur6 be as specific as possible so we can help you more quickly we will get back to you with follow up questions or a link for booking a timeslot additional information div align center img src static img web svg s 50 width 50 img img src static img twitter svg s 50 width 50 img img src static img learn svg s 50 width 50 img img src static img wiki svg s 50 width 50 img img src static img youtube svg s 50 width 50 img w3f website https web3 foundation w3f twitter https twitter com web3foundation w3f medium https medium com web3foundation polkadot wiki https wiki polkadot network en w3f youtube https www youtube com channel uclnw bcng4cazf772qetq4g div rocket alternative funding sources we encourage you to explore the alternative funding options listed below please note however that you should not seek to fund the same scope of work from multiple sources and that any team found doing so will have its web3 foundation support terminated substrate builders program vs treasury vs web3 grants the following flowchart gives a rough oversimplified view of how the w3f grants program the polkadot and kusama treasuries and parity s substrate builders program relate and where your project might fit best note that this diagram does not include any of the parachain specific grants builders programs other grant programs other organisations are offering mermaid flowchart lr a project focus a development b stage of development a research c grants program a other d treasury b existing poc e goal of the application b no poc f grants program e funding g treasury or grants program e support h substrate builders program style c stroke e83e8c stroke width 2px stroke dasharray 5 5 style d stroke e83e8c stroke width 2px stroke dasharray 5 5 style f stroke e83e8c stroke width 2px stroke dasharray 5 5 style h stroke e83e8c stroke width 2px stroke dasharray 5 5 click c https github com w3f grants program pencil process you are already in the right place click d https polkadot network treasury https polkadot network treasury blank click f https github com w3f grants program pencil process you are already in the right place click h https www substrate io builders program https www substrate io builders program blank substrate builders program the substrate builders program https substrate io ecosystem substrate builders program directly supports you by connecting you with parity s extensive resources treasury the treasury is a pot of on chain funds collected through transaction fees slashing staking inefficiencies etc the funds held in the treasury can be spent on spending proposals both polkadot https polkadot network and kusama https kusama network offer everyone the opportunity to apply for funding via the treasury see treasury https polkadot network treasury treasury bounties https polkadot subsquare io treasury bounties polkadot treasury guide https docs google com document d 1izykdp2cyqavcryzd dgnj5dcgxgzr6kaqgdcnaru1w kusama treasury guide https docs google com document d 1p3uqujph5t8tvawntkfri5me babnm9xvtuhdlhl6je hackathons from time to time web3 foundation and or parity organise hackathons to promote quick prototyping of polkadot related ideas we highly encourage you to participate in these hackathons bear in mind however that you cannot submit the same work for a hackathon and the grants program if you have worked or are planning to work on a project for a hackathon your grant application should either propose a different set of features or otherwise build on top of your hackathon work the same applies in reverse although that will likely be less common the best way to find out about upcoming hackathons is by following polkadot on various social channels such as element or twitter other grant or bounty programs below is a list of other grant and bounty programs in the polkadot substrate ecosystem acala grants program https acala network ecosystem program aleph zero funding program https alephzero org ecosystem funding program astar shiden network builders program https github com plasmnetwork builders program crust grants program https github com crustio crust grants program darwinia grants program https github com darwinia network collaboration blob master grant readme md grant program edgeware grants and bounties https gov edgewa re discussion 1132 edgeware proposal process and template hydradx grants and bounties https docs hydradx io spending fw ink ubator https use ink ubator interlay labs grants program https github com interlay grants program kodadot ecosystem grants https github com kodadot grants moonbeam grants program https moonbeam foundation grants oak s developer grants https oak tech community grants peaq ecosystem grant program https www peaq network grant program phala builders program https wiki phala network en us build general builders program picasso composable grants program https docs composable finance ecosystem composable grants polkadot pioneers prize https pioneersprize polkadot network subquery grants programme https subquery network grants pendulum amplitude grant programs https pendulumchain org ecosystem grant information source license omit in toc apache license 2 0 license web3 foundation | blockchain polkadot substrate kusama | blockchain |
annotated-webpack-config | annotated webpack 4 config this is the companion github repo for the an annotated webpack 4 config for frontend web development https nystudio107 com blog an annotated webpack 4 config for frontend web development article it contains the full webpack config and ancillary files discussed in the article please see the article for details | annotated webpack webpack4 config frontend development javascript nodejs | front_end |
XVERSE-7B | div align center h1 xverse 7b h1 div p align center a href https huggingface co xverse xverse 7b xverse 7b a nbsp nbsp a href https huggingface co xverse xverse 7b chat xverse 7b chat a nbsp nbsp a href https modelscope cn organization xverse rel nofollow img src resources modelscope png width 20px style max width 100 modelscope a nbsp nbsp a href resources wechat png a p h4 align left p b b a href readme en md english a p h4 xverse 7b large language model 70 xverse 7b xverse 7b chat xverse 7b decoder only transformer 8k context length 2 6 token 40 bpe byte pair encoding gb 100 534 58 5 mmlu https arxiv org abs 2009 03300 c eval https cevalbenchmark com agieval https arxiv org abs 2304 06364 gaokao bench https github com openlmlab gaokao bench gaokao english https github com expressai ai gaokao mmlu c eval agieval sup 1 sup gaokao bench sup 1 sup gaokao english sup 1 sup baichuan 7b 42 3 sup 2 sup 42 8 sup 2 sup 34 4 sup 2 sup 36 3 sup 2 sup 44 3 baichuan2 7b base 54 2 sup 2 sup 54 0 sup 2 sup 42 7 sup 2 sup 47 5 sup 2 sup 53 1 baichuan2 7b chat 53 2 52 2 41 3 49 7 66 6 chatglm2 6b 45 5 sup 2 sup 50 1 sup 2 sup 42 6 54 2 59 7 falcon 7b 27 8 sup 2 sup 25 8 26 2 26 3 29 9 internlm 7b 51 0 sup 2 sup 52 4 34 1 53 6 32 3 internlm 7b chat 50 8 sup 2 sup 52 8 39 0 67 4 43 9 llama 7b 35 1 sup 2 sup 27 0 27 4 26 0 30 1 llama 2 7b 45 3 sup 2 sup 28 9 27 0 27 8 47 8 mpt 7b 29 6 sup 2 sup 27 8 24 2 25 3 28 1 vicuna 7b v1 5 49 8 sup 2 sup 22 9 26 7 24 4 61 1 xverse 7b 56 6 57 1 46 9 61 7 71 1 xverse 7b chat 63 7 55 4 48 9 57 5 78 2 sup 1 sup sup 2 sup mmlu https github com hendrycks test c eval agieval gaokao bench gaokao english mmlu 5 shot mmlu average stem social science humanities others baichuan 7b 42 3 35 6 48 9 38 4 48 1 baichuan2 7b chat 53 2 43 1 59 1 50 0 59 1 chatglm2 6b 45 5 40 1 51 6 41 2 51 2 internlm 7b 51 0 58 7 43 5 52 7 53 2 llama 7b 35 1 30 5 38 3 34 0 38 1 llama2 7b 45 3 36 4 51 2 42 9 52 2 xverse 7b 56 6 45 6 65 3 50 4 65 5 xverse 7b chat 63 7 51 7 72 5 58 2 72 2 c eval average stem social science humanities others baichuan 7b 42 8 38 2 52 0 46 2 39 3 baichuan2 7b base 54 9 47 9 67 3 58 4 52 8 baichuan2 7b chat 52 2 44 6 65 0 55 8 50 9 chatglm2 6b 50 1 46 4 60 4 50 6 46 9 falcon 7b 25 8 25 8 26 0 25 8 25 7 internlm 7b 52 4 47 0 64 9 55 6 47 6 internlm 7b chat 52 8 48 4 65 6 57 0 45 0 llama 7b 27 0 26 7 26 7 28 4 26 2 llama2 7b 28 9 26 8 34 5 30 0 26 4 mpt 7b 27 8 27 4 29 8 26 9 27 7 vicuna 7b v1 5 22 9 21 8 23 3 24 0 23 3 xverse 7b 57 1 48 9 71 0 59 7 56 7 xverse 7b chat 55 4 47 9 68 5 57 3 55 1 1 shell git clone https github com xverse ai xverse 7b cd xverse 7b 2 pip shell pip install r requirements txt transformers xverse 7b chat python import torch from transformers import autotokenizer automodelforcausallm from transformers generation utils import generationconfig model path xverse xverse 7b chat tokenizer autotokenizer from pretrained model path model automodelforcausallm from pretrained model path trust remote code true torch dtype torch bfloat16 device map auto model generation config generationconfig from pretrained model path model model eval history role user content 1955 response model chat tokenizer history print response 1955 d history append role assistant content response history append role user content response model chat tokenizer history print response d 1953 1961 8 demo web server xverse 7b chat shell python chat demo py port port model path path to model tokenizer path path to tokenizer xverse 7b chat chat demo py xverse 7b chat details summary b b summary xverse 7b chat xverse 7b chat xverse 7b chat xverse 7b chat xverse 7b chat details details summary b b summary xverse 7b chat details details summary b b summary 5 xverse 7b chat 180 90 70 230 40 details details summary b b summary xverse 7b chat python def quicksort arr if len arr 1 return arr pivot arr len arr 2 left x for x in arr if x pivot middle x for x in arr if x pivot right x for x in arr if x pivot return quicksort left middle quicksort right print quicksort 3 6 8 10 1 2 1 output 1 1 2 3 6 8 10 1 left middle right left middle right details details summary b b summary 3 3 60 xverse 7b chat 60 x 3 180 180 x 3 540 details details summary b b summary xverse 7b chat details details summary b b summary n n 201 n n n xverse 7b chat details details summary b b summary how many legs does a horse have xverse 7b chat a horse has four legs xverse 7b chat combien de pattes a un cheval xverse 7b chat un cheval a quatre pattes xverse 7b chat 4 details details summary b b summary xverse 7b chat details int8 int4 int8 python model automodelforcausallm from pretrained xverse xverse 7b chat torch dtype torch bfloat16 trust remote code true model model quantize 8 cuda int4 python model automodelforcausallm from pretrained xverse xverse 7b chat torch dtype torch bfloat16 trust remote code true model model quantize 4 cuda mmlu gb mmlu xverse 7b chat bf16 fp16 16 2 63 7 xverse 7b chat int8 9 1 63 5 xverse 7b chat int4 5 9 56 1 xverse 7b xverse 7b chat llama efficient tuning https github com hiyouga llama efficient tuning xverse 7b 8 nvidia a800 80 gb deepspeed llama efficient tuning https github com hiyouga llama efficient tuning getting started model path xverse 7b xverse 7b chat bfloat16 bfloat16 bash deepspeed num gpus 8 src train bash py stage sft model name or path model path do train dataset alpaca gpt4 en template default finetuning type full output dir output model path overwrite cache per device train batch size 4 per device eval batch size 4 gradient accumulation steps 4 preprocessing num workers 16 lr scheduler type cosine logging steps 10 save steps 200 eval steps 200 learning rate 2e 5 max grad norm 0 5 num train epochs 2 0 evaluation strategy steps load best model at end plot loss bf16 padding side right deepspeed deepspeed json deep speed json json train micro batch size per gpu auto gradient accumulation steps auto gradient clipping auto zero allow untested optimizer true bf16 enabled true zero optimization stage 2 allgather partitions true reduce scatter true overlap comm false contiguous gradients true xverse 7b llm xverse 7b xverse 7b xverse 7b apache 2 0 license xverse 7b model license pdf xverse 7b opensource xverse cn | ai |
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2018_ee832n | 2018 ee832n charlie s ee382n advanced embedded system design hw and labs | os |
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Embedded | this repository is created for an embedded system design the functionality of the codes are simulated on ek tm4c123gxl with arm cortex m4f mcu | os |
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sql-challenge | project description examine what remains of an employee database of people that a fictional company employed during the 1980s and 1990s an entity relationship diagram employee erd png was created to visualise the relationship between the six csv files that made up the employee database table schemata were created for each csv file results of analysis are published in the employeesql folder the following queries were conducted 1 list the employee number last name first name sex and salary of each employee 2 list first name last name and hire date for employees who were hired in 1986 3 list the manager of each department with the following information department number department name the manager s employee number last name first name 4 list the department of each employee with the following information employee number last name first name and department name 5 list first name last name and sex for employees whose first name is hercules and last names begin with b 6 list all employees in the sales department including their employee number last name first name and department name 7 list all employees in the sales and development departments including their employee number last name first name and department name 8 list the frequency counts in descending order of all the employees last names figures created 1 histogram that visualises employee salary ranges salary distribution png 2 bar chart of average salary by title average salary by title png packages dependencies used postgresql pandas matplotlib pyplot numpy psycopg2 folder contents in employeesql folder employee erd png image file of entity relationship diagram of csv files in data folder schema sql sql file of table schemata queries sql sql file of queries employee bonus ipynb jupyter notebook for bonus analysis salary distribution png histogram that visualises employee salary ranges average salary by title png bar chart of average salary by title in data folder departments csv dept emp csv dept manager csv employees csv salaries csv titles csv | server |
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vue-cion-design-system | cion design system boilerplate for vue js cion is a design system build primarily for vue js applications you can use it as a starting point for building your own design system the system utilizes design tokens a living styleguide with integrated code playgrounds and reusable components for common ui tasks living styleguide demo https styleguide cion visualjerk de landing page demo https cion visualjerk de integrate it in your application usage https cion visualjerk de usage screenshot preview customize png https github com visualjerk vue cion design system raw master preview customize png project setup yarn install developing compiles and hot reloads living styleguide yarn dev building living styleguide compiles living styleguide to docs yarn build library compiles design system as a library to dist yarn build lib helper serve living styleguide locally yarn serve lints and fixes files yarn lint projects that use cion human connection styleguide https styleguide human connection org license mit license license copyright c j rg bayreuther | vue design-system design-tokens livingstyleguide living-documentation vuejs components design-systems | os |
google-cloud | google cloud course notes https www coursera org professional certificates cloud engineering gcp | cloud |
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Raspberry_Pi3_FreeRTOS | freertos raspberry pi3 bcm2837 building get the compiler gcc arm none eabi 4 7 2013q3 20130916 win32 exe or download it from my google drive install it when it asks environment variable just skip it https drive google com open id 1 0cy zfqs9tjbsg7oknkmi w69grhnu c program files x86 gnu tools arm embedded 4 7 2013q3 bin gccvar bat run this may be you can make a shortcut to desktop move to the folder my project files are copied in d drive folder d enter cd path enter type make linux mac users install suitable compiler enter make freertos demo creates 2 tasks one controls led other prints text connect to usb uart to see task status attached working kernel img image bootloader files for hands on works only on raspberry pi3 or bcm2837 | os |
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building-mobile-apps-flex | building mobile apps flex short description this is the source code samples and documentation from the esri developer summit 3 technical workshop session building mobile applications with the arcgis api for flex 1 long description in this session we show you how easy it is to use flex to deploy native mobile mapping applications on apple ios and google android we ll cover considerations for mobile versus web development and explore topics such as map performance events multiple views as well as handling gesture orientation changes and we ll also cover debugging tips thumbnail with hyperlink screenshot wiki assets building mobile apps flex png screenshot wiki view this recorded session 2 from the esri developer summit 3 repository description this repository includes the source code from the samples and apps demonstrated in the technical workshop read the documentation wiki for getting started using this repository requirements knowledge of flex development a little background with adobe apache flex sdk experience with the arcgis api for flex http links esri com flex would help resources arcgis api for flex resource center http links esri com flex flex api license agreement http www esri com legal pdfs mla e204 e300 english pdf arcgis blog http blogs esri com esri arcgis tag flex agup http twitter com agup lheberlie http twitter com lheberlie yanncabon http twitter com yanncabon issues find a bug or want to request a new feature please let us know by submitting an issue issues contributing anyone and everyone is welcome to contribute contributing md licensing copyright 2013 esri licensed under the apache license version 2 0 the license you may not use this file except in compliance with the license you may obtain a copy of the license at http www apache org licenses license 2 0 unless required by applicable law or agreed to in writing software distributed under the license is distributed on an as is basis without warranties or conditions of any kind either express or implied see the license for the specific language governing permissions and limitations under the license a copy of the license is available in the repository s license txt https raw github com esri arcgis viewer flex master license txt file 1 http events esri com bpc 2013 dev agenda index cfm fa session detail form sessionid 132 scheduleid 236 2 http video esri com watch 2298 building mobile applications with arcgis api for flex 3 http www esri com devsummit | front_end |
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itscience | information technology science standard xi open source based book chapters 1 introduction to information technology 2 office suite 3 multimedia 4 web browsers email clients messanger utilities 5 introduction to networking 6 visual basic net need to change to open source programming 7 html 8 introduction to javascript use following link to learn how to write this document https github com adam p markdown here wiki markdown cheatsheet | server |
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mcv-m5 | mcv m5 master in computer vision m5 visual recognition fork this project fork this project to start your group project add robertbenavente https github com robertbenavente and lluisgomez https github com lluisgomez as contributors project description download the overleaf document https www overleaf com read qrjbtzwtjhmx project slides google slides for week 1 https docs google com presentation d 1a6hgbnn8n iq8mhsa rpiyf87dbl6pctodzy1zqs5xs edit usp sharing google slides for week 2 https docs google com presentation d 1q69lmzpzgtc4ldw8dr9yyfy t9jxhjjgl4shyxfjk3m edit usp sharing google slides for week 3 https docs google com presentation d 1wuzvetwul65dnki3vsbjghxwkffrfanwxbmr urklqq edit usp sharing google slides for week 5 https docs google com presentation d 1nb4tfrm1swddqzbr0aduv7t4p4f7t3guzdt5q psmmk edit usp sharing google slides for week 7 t b a peer review intra group evaluation form for week 2 t b a intra group evaluation form for weeks 3 4 t b a intra group evaluation form for weeks 5 6 t b a intra group evaluation form for week 7 t b a news improve your github account following this document https docs google com document d 14oxskwbbmajib5bn2cm dnb vychy1f393qyfshnjfy edit usp sharing groups group 01 https github com guillemdelgado mcv m5 francisco rold n s nchez guillem delgado gonzalo jordi gen mola group 02 https github com rogermm14 mcv m5 roger mar molas joan sintes marcos alex palomo dominguez alex vicente sola group 04 https github com mcvavteam mcv m5 mikel menta garde alex valles fernandez sebastian camilo maya hern ndez pedro luis trigueros mond jar group 05 https github com marc gorriz mcv m5 guillermo eduardo torres marc g rriz blanch cristina maldonado moncada group 06 https github com yixiao1 mcv m5 juan felipe montesinos garcia ferran carrasquer mas yi xiao group 07 https github com arnauvallve94 mcv m5 yevgeniy kadranov santiago barbarisi arnau vallv gispert group 08 https github com jonpoveda scene understanding for autonomous vehicles ferran p rez gamonal joan francesc serracant lorenzo jonatan poveda pena mart cobos arnalot group 09 https github com bourboncreams mcv m5 lorenzo betto noa mor ana caballero cano ivan caminal colell | ai |
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bio-cli | mac available https img shields io badge mac available brightgreen svg windows unavailable https img shields io badge windows unavailable red svg node version https img shields io badge node 3e 3d 208 9 1 brightgreen svg http nodejs org npm version https img shields io badge npm 3e 3d 205 5 1 brightgreen svg https www npmjs com website https weidian inc github io bio cli contributors core hoperyy https github com hoperyy lint ioriens https github com ioriens license mit | front_end |
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front-end-guidelines | front end developer guidelines about this project this project introduces a comprehensive new style guide and css architecture that front end devs should use in all projects going forwards the style guide section currently only covers css and will be extended to include html and javascript in the future this project will soon be set up in such a way that it can be downloaded and used to kick start new projects this process is intended to be easy to modify scale evolve and adapt so your thoughts concerns and recommendations are appreciated and requested i don t want anyone to feel forced to use this but it should be immediately apparent that it is a great way to work i m sure you ll agree that we re in need of a bit of consistency regarding front end code quality and project setup especially since we are truly global now ideally we want to move away from frameworks such as bootstrap and foundation they may be great for prototyping but i find they interfere too much and bloat a full website build this may sound like a framework itself but it s more of a folder structure and set of guidelines it does however include the mixin library that benn and i have put together but this aims to include only useful features that the majority of projects are likely to use you re free to add your own project specific tools if you wish key benefits allows for mobile first component based development uses the css cascade to full effect via the logical import order of css partials backend agnostic which is great for company wide consistency easy to maintain and scale through consistent structure and simple modular css partials with inline media queries rather than separate stylesheets for each breakpoint works with sass less or even plain css if you re mental i ve used sass and scss in the information below contents 1 asset folder structure asset folder structure 1 general general 2 css css 3 images images 4 javascript javascript 5 type type 2 css architecture css architecture 1 css folder structure css folder structure 2 css source order css source order 3 css style guide css style guide a name asset folder structure a asset folder structure assets css sass settings all scss color scss type scss vars scss tools helpers clearfix scss hide text scss image replacement scss image retina scss prefixer scss mixins font face scss media query hidpi scss media query scss prefix scss transform scss transition scss functions em calc scss grid flex scss percentage scss strip units scss all scss generic all scss normalize scss reset scss base all scss form elements scss headings scss links scss page scss objects all scss buttons scss components all scss nav primary scss trumps all scss helpers scss print scss app scss app css blank example file app min css blank example file img contains blank example files frame logo client png content placeholder image rte jpg js vendor contains blank example files jquery 1 11 0 min js jquery bxslider 4 1 2 min js jshintrc app js blank example file app min js blank example file type contains blank example files project icons eot project icons svg project icons ttf project icons woff selection json non blank example file gitattributes gitignore readme md a name general a general all folder names should be lowercase and use hyphens underscores or periods instead of spaces if you re using mixture converted html should be added to gitignore compiled minified css and custom minified javascript should be added to gitattributes as binary files e g assets css min css binary assets js min js binary this is to avoid potential merge conflicts and large diffs compiled but non minified css should be added to gitignore this is to keep it out of the repository and prevent backend from mistakenly editing the css directly naming all assets and classes should be lowercase no camelcase and use a bem http bem info ish naming convention which goes from general to specific block element modifier element is used to show that the element is inside or dives down into a block e g nav class nav ul li class nav item a href float me left a li li class nav item a href float me left a li li class nav item alt a href float me right a li ul nav modifier can be applied to a block or an element e g nav class nav secondary ul li class nav secondary item a href float me left a li li class nav secondary item a href float me left a li li class nav secondary item alt a href i ve got a border a li ul nav double and are used so that single or can be used when naming a block element or modifier e g social links small the class name given to a component or object should be as general as possible but it should still make sense to a developer you should be able to tell which component you are editing and what that component does just by looking at the html or css and not the page in browser keeping the name general means that a component can be placed anywhere on a site and its name is not affected by the context home slider is bad because if the same slider is used somewhere other than the home page the name no longer makes sense carousel primary is better you can then use secondary tertiary alpha beta etc to name similar components a name css a css jump to the css architecture css architecture section for detailed information on the css folder structure and style guide a name images a images any images that are not suitable for packaging into the project icon font see type type below that are used primarily in your css such as the logo or custom map markers should be placed within assets img frame content image placeholders should be placed within assets img content images should be compressed saving jpg images using photoshop s save for web and devices option at 60 works well in most cases png images can be compressed losslessy using a program like pnggauntlet http pnggauntlet com for windows or imageoptim http imageoptim com for mac naming image type image name ext e g logo project png icon map pin png placeholder image profile card jpg a name javascript a javascript third party javascript files should be minified and placed inside assets js vendor custom javascript is written in assets js app js which is minified as assets js app min js add this to gitattributes as binary remember custom javascript should be checked with jshint http www jshint com install or similar sublime text http www sublimetext com has a jshint plugin available which allows you to create a per project jshintrc configuration file that should be added to your project s gitignore naming library plugin v e r min js e g modernizr 2 8 1 min js a pure javascript file that doesn t require a library like jquery jquery bxslider 4 1 2 min js javascript files that require libraries should be prefixed with the library name e g jquery a name type a type web fonts should be placed inside assets type suitable icons i e vector should be packaged into an icon font using icomoon icomoon io this app can be used to generate a selection json file that is placed within assets type and added to git this file contains all the settings and info necessary to make it easy for developers to add remove or edit icons used in the project naming font name font variant ext e g freight sans medium ttf a name css architecture a css architecture a name css folder structure a css folder structure the folder structure for css is based on harry roberts http csswizardry com css architecture for big front ends i attended his workshop at the future of web design 2014 http futureofwebdesign com london 2014 conference and it was outstanding this is a key part of the new style guide and requires a solid explanation please let me know if anything is confusing or doesn t make sense here s the folder structure again with notes on key elements css contains all sass and compiled css files sass settings project variables all scss all scss files import the others in the same folder so this one file can be imported into the main app scss file color scss type scss vars scss tools the precedent mixin library helpers helper mixins for common tasks clearfix scss hide text scss image replacement scss image retina scss prefixer scss mixins mixins for css3 features font face scss media query hidpi scss media query scss prefix scss transform scss transition scss functions handy functions em calc scss grid flex scss percentage scss strip units scss all scss this file imports all tools generic resets and normalize all scss normalize scss reset scss base styling that targets plain html elements usually no classes in here all scss form elements scss headings scss links scss page scss objects basic design patterns and re usable abstractions all scss accordion scss buttons scss components styled components and modules all scss accordion primary scss trumps overrides these usually have important rules and that s okay they come last and they re designed to take precedence over all other styles all scss helpers scss float right mobile only etc print scss print styles are typically overriding everything that came befroe app scss this file imports every all scss partial listed above in the order shown very important app css this is the expanded compiled css with comments app min css this is the minified compiled css mixture handles these two this is the only css file that should be delivered for back end integration a name css source order a css source order the css structure and import order is important and goes from general affecting many elements to specific affecting just one element in one circumstance for example 1 settings variables feature switches and other project specific settings these are defined first and will be picked up and used by the framework later on 2 tools mixins and functions to make tasks easier these appear early on so that they can be utilised in the main body of the codebase 3 generic resets global box sizing these styles are really far reaching they underpin every element we place on the page 4 base base elements unclassed h1 ol etc these are semantic html elements that require some base styling for when they exist outside of a component context e g a regular bulleted list in some body copy 5 objects design patterns objects abstractions and constructs 6 components styled components and modules these build on top of semantic html elements and are referred to mainly through class selectors 7 trumps style trumps helper classes and overrides these need to override any other styles and thus come last it is common for these styles to be important the idea is that css is imported and parsed in the browser in a logical order from general styles to very specific so you re typically adding style rules instead of taking them away a name css style guide a css style guide general sass partials should be prefixed with an underscore object and component partials should match the main class name that they reference e g nav primary scss compiled minified css should be added to gitattributes as binary files e g assets css min css binary compiled but non minified css should be added to gitignore this is to keep it out of the repository and prevent backend from mistakenly editing the css directly writing rules write css mobile first do not use ids unless you re overriding something a cms has spat out and you can t add a class to the element one selector per line put a single space before put a single space after no space before use after every declaration separate rules by blank lines except when rules are nested use short hex color codes 000 or rgba use shorthand notation where possible use for comments use single quotes instead of double quotes use before and after put a single space after commas omit the 0 when entering decimals between 0 and 1 omit units after 0 values omit units from line height avoid qualifying class names with an element selector e g div primary do not use quotes in urls use 4 spaces for indentation use em for font sizes set body font size to the standard paragraph size from the psd not 62 5 use the sass em calc function to set px font sizes that are converted to em once compiled use box sizing border box globally if possible use for widths use px for padding and margins use bottom 100 or top 100 instead of magic numbers e g top 177px place active classes for navigation on the li not the a nest media queries within the parent or top level selector declaration order declare styles in this order 1 extends 2 includes mixins 3 standard rules 4 media queries a name example a full example example example large extend heading include clearfix border 1px solid 000 color rgba 0 0 0 5 background url assets img placeholder image example jpg no repeat center padding 0 remove padding font size em 20px p color f00 media query desktop font size em 22px p color f0f example special border 1px solid f00 nesting nesting should be kept to a minimum it s fine to nest component css where it makes sense but think about the compiled css and only nest as deep as you would if you were to write out the full selector in plain css i e don t do this nav primary nav primary menu nav primary item color red or ul li color pink which compiles to the overly specific nav primary nav primary menu nav primary item color red or nav primary ul li color pink you wouldn t write plain css like that and it would be hard to override do this instead nav primary styles nav primary menu styles nav primary item styles separating all components into individual partials will keep css grouped and easy to navigate looking at the compiled css in dev tools and trying to work out where the style is declared should no longer be a problem having sensible classes on every possible element within a component allows you to avoid over nesting and means in many cases selectors are only a single class this is great and easy to override if necessary additionally styling based on classes instead of elements like li or a means that the html element can change and the styling will still apply it may not always be possible to have that level of control however so you can fall back to targeting a parent class and plain html elements e g nav primary li nav primary a writing your css in this way though will naturally result in more nested styles if you re using this style it can be a good idea to tightly scope your selectors using the direct child selector | front_end |
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