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https://github.com/RobertMyles/awesome-stars
A curated list of my GitHub stars!
https://github.com/RobertMyles/awesome-stars
List: awesome-stars
Last synced: 3 days ago
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A curated list of my GitHub stars!
- Host: GitHub
- URL: https://github.com/RobertMyles/awesome-stars
- Owner: RobertMyles
- Created: 2019-11-09T11:18:46.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2019-11-09T11:18:48.000Z (about 5 years ago)
- Last Synced: 2024-04-25T00:17:16.358Z (7 months ago)
- Homepage:
- Size: 31.3 KB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Awesome Stars [](https://github.com/sindresorhus/awesome)
> A curated list of my GitHub stars! Generated by [starred](https://github.com/maguowei/starred)
## Contents
- [Assembly](#assembly)
- [C](#c)
- [C#](#c#)
- [C++](#c++)
- [CSS](#css)
- [Cuda](#cuda)
- [Go](#go)
- [HTML](#html)
- [Haskell](#haskell)
- [Java](#java)
- [JavaScript](#javascript)
- [Jupyter Notebook](#jupyter-notebook)
- [Lua](#lua)
- [Makefile](#makefile)
- [Others](#others)
- [PHP](#php)
- [Perl](#perl)
- [PowerShell](#powershell)
- [Python](#python)
- [QML](#qml)
- [R](#r)
- [Rich Text Format](#rich-text-format)
- [Roff](#roff)
- [Ruby](#ruby)
- [Rust](#rust)
- [Shell](#shell)
- [Stan](#stan)
- [Stata](#stata)
- [Swift](#swift)
- [TeX](#tex)
- [TypeScript](#typescript)
## Assembly
- [pics](https://github.com/corkami/pics) - Posters, drawings...
- [cjdns](https://github.com/cjdelisle/cjdns) - An encrypted IPv6 network using public-key cryptography for address allocation and a distributed hash table for routing.
## C
- [ngram](https://github.com/wrathematics/ngram) - Fast n-Gram Tokenization
- [meshroom](https://github.com/hypertidy/meshroom) -
- [uwimg](https://github.com/pjreddie/uwimg) - Build your own computer vision library in C
- [data.table](https://github.com/Rdatatable/data.table) - R's data.table package extends data.frame:
- [antiword](https://github.com/ropensci/antiword) - R wrapper for antiword utility
- [qs](https://github.com/traversc/qs) - Quick serialization of R objects
- [japronto](https://github.com/squeaky-pl/japronto) - Screaming-fast Python 3.5+ HTTP toolkit integrated with pipelining HTTP server based on uvloop and picohttpparser.
- [BAS](https://github.com/merliseclyde/BAS) - BAS R package
- [Probabilistic-Backpropagation](https://github.com/HIPS/Probabilistic-Backpropagation) - Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
- [sys](https://github.com/jeroen/sys) - Powerful replacements for base::system2
- [ore](https://github.com/jonclayden/ore) - An R interface to the Onigmo regular expression library
## C# #
- [UnityWorker](https://github.com/OpenMined/UnityWorker) - DEPRECATED
- [RserveCLI2](https://github.com/konne/RserveCLI2) - A fork of RServeCLI
## C++
- [tensorflow](https://github.com/tensorflow/tensorflow) - An Open Source Machine Learning Framework for Everyone
- [css](https://github.com/romainfrancois/css) - tidy css manipulation
- [Dawn-of-Civilization](https://github.com/dguenms/Dawn-of-Civilization) - The Dawn of Civilization mod for Civilization IV: Beyond the Sword, based on the popular Rhye's and Fall of Civilization mod.
- [ryacas](https://github.com/mikldk/ryacas) - Ryacas: R Interface to the Yacas Computer Algebra System
- [ryacas0](https://github.com/mikldk/ryacas0) - Ryacas0: Legacy version of Ryacas (R Interface to the Yacas Computer Algebra System)
- [cppRouting](https://github.com/vlarmet/cppRouting) - Fast implementation of Dijkstra algorithm in R
- [dodgr](https://github.com/ATFutures/dodgr) - Distances on Directed Graphs in R
- [rayrender](https://github.com/tylermorganwall/rayrender) - A raytracer for R. Based on Peter Shirley's "Ray Tracing in One Weekend" book series.
- [differential-privacy](https://github.com/google/differential-privacy) - Google's C++ differential privacy library.
- [ngraph](https://github.com/NervanaSystems/ngraph) - nGraph - open source C++ library, compiler and runtime for Deep Learning
- [HElib](https://github.com/homenc/HElib) - An Implementation of homomorphic encryption
- [tfhe](https://github.com/tfhe/tfhe) - TFHE: Fast Fully Homomorphic Encryption Library over the Torus
- [PySEAL](https://github.com/Hamurabbi/PySEAL) - A simple python SEAL wrapper. This one is easier to just build and use, compared to the dockerized versions available
- [libdart](https://github.com/target/libdart) - A High Performance, Network Optimized, JSON Library
- [interpret](https://github.com/interpretml/interpret) - Fit interpretable models. Explain blackbox machine learning.
- [SEAL](https://github.com/microsoft/SEAL) - Microsoft SEAL is an easy-to-use and powerful homomorphic encryption library.
- [he-transformer](https://github.com/NervanaSystems/he-transformer) - nGraph-HE: Deep learning with Homomorphic Encryption (HE) through Intel nGraph
- [glow](https://github.com/pytorch/glow) - Compiler for Neural Network hardware accelerators
- [serving](https://github.com/tensorflow/serving) - A flexible, high-performance serving system for machine learning models
- [PySEAL](https://github.com/Lab41/PySEAL) - This repository is a fork of Microsoft Research's homomorphic encryption implementation, the Simple Encrypted Arithmetic Library (SEAL). This code wraps the SEAL build in a docker container and provides Python API's to the encryption library.
- [vroom](https://github.com/r-lib/vroom) - Fast reading of delimited files
- [torch](https://github.com/dfalbel/torch) - torch from R!
- [catboost](https://github.com/catboost/catboost) - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
- [grf](https://github.com/grf-labs/grf) - Generalized Random Forests
- [geojsonsf](https://github.com/SymbolixAU/geojsonsf) - Conversion between sf and geojson
- [imagerstreams](https://github.com/dahtah/imagerstreams) -
- [horovod](https://github.com/horovod/horovod) - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
- [JuniperKernel](https://github.com/JuniperKernel/JuniperKernel) - R Kernel for Jupyter
- [geogrid](https://github.com/jbaileyh/geogrid) - Turning geospatial polygons into regular or hexagonal grids
- [poster](https://github.com/Ironholds/poster) - Address parsing and normalisation through libpostal
- [archive](https://github.com/jimhester/archive) - R bindings to libarchive, supporting a large variety of archive formats
- [feather](https://github.com/wesm/feather) - Feather: fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow
- [DeepSpeech](https://github.com/mozilla/DeepSpeech) - A TensorFlow implementation of Baidu's DeepSpeech architecture
- [qmf](https://github.com/quora/qmf) - A fast and scalable C++ library for implicit-feedback matrix factorization models
- [later](https://github.com/r-lib/later) - Schedule an R function or formula to run after a specified period of time.
- [rcppbugs](https://github.com/armstrtw/rcppbugs) - R interface for CppBugs
## CSS
- [markdowntemplates](https://github.com/hrbrmstr/markdowntemplates) - :white_check_mark::small_red_triangle_down: A collection of alternate R markdown templates
- [supervised-ML-case-studies-course](https://github.com/juliasilge/supervised-ML-case-studies-course) - Supervised machine learning case studies in R! ๐ซ A free interactive course
- [style](https://github.com/tidyverse/style) - The tidyverse style guide for R code
- [gams-in-r-course](https://github.com/noamross/gams-in-r-course) - Generalized Additive Models in R: A Free Interactive Course
- [rmdcss](https://github.com/nwstephens/rmdcss) - CSS templates for R Markdown documents
- [typefaces](https://github.com/KyleAMathews/typefaces) - NPM packages for Open Source typefaces
- [learn.scrapinghub.com](https://github.com/scrapinghub/learn.scrapinghub.com) - Scrapinghub Learning Center. Report issues in Jira: Report issues in Jira: https://scrapinghub.atlassian.net/projects/WEB
- [CausalModeling](https://github.com/pedrosan/CausalModeling) -
- [CrookedStyleSheets](https://github.com/jbtronics/CrookedStyleSheets) - Webpage tracking only using CSS (and no JS)
- [nord](https://github.com/arcticicestudio/nord) - An arctic, north-bluish color palette.
- [picnic](https://github.com/franciscop/picnic) - :handbag: A beautiful CSS library to kickstart your projects
- [typi](https://github.com/zellwk/typi) - A sass mixin to make responsive typography easy
## Cuda
- [deep-painterly-harmonization](https://github.com/luanfujun/deep-painterly-harmonization) - Code and data for paper "Deep Painterly Harmonization": https://arxiv.org/abs/1804.03189
## Go
- [lazygit](https://github.com/jesseduffield/lazygit) - simple terminal UI for git commands
- [flotilla-os](https://github.com/stitchfix/flotilla-os) - Open source Flotilla
- [aresdb](https://github.com/uber/aresdb) - A GPU-powered real-time analytics storage and query engine.
- [gron](https://github.com/tomnomnom/gron) - Make JSON greppable!
- [annie](https://github.com/iawia002/annie) - ๐พ Fast, simple and clean video downloader
- [micro](https://github.com/zyedidia/micro) - A modern and intuitive terminal-based text editor
## HTML
- [ScPoEconometrics](https://github.com/ScPoEcon/ScPoEconometrics) - Undergraduate textbook for Econometrics with R
- [lgr](https://github.com/s-fleck/lgr) - A fully featured logging framework for R
- [introcausality](https://github.com/NickCH-K/introcausality) - Class materials for "Economics, Causality, and Analytics"
- [bayestime](https://github.com/prior-knowledge/bayestime) - a course on bayesian statistics from probability to multilevel models with stan
- [vip](https://github.com/koalaverse/vip) - Variable importance plots
- [example-rmd-templates](https://github.com/dr-harper/example-rmd-templates) - ๐ A selection of minimal examples used to highlight R Markdown templates, as referred to in the "R Markdown Definitive Guide"
- [svm-r-markdown-templates](https://github.com/svmiller/svm-r-markdown-templates) - I have a suite of R Markdown templates for academic manuscripts, beamer presentations, and syllabi. I share them here.
- [datascience-box](https://github.com/rstudio-education/datascience-box) - Data Science Course in a Box
- [learndrake](https://github.com/wlandau/learndrake) - An interactive workshop on drake
- [ggchicklet](https://github.com/hrbrmstr/ggchicklet) - ๐ซ Create Chicklet (Rounded Segmented Column) Charts
- [oshka](https://github.com/brodieG/oshka) - Simple Programmable R NSE
- [PM_VEE](https://github.com/pbiecek/PM_VEE) - Predictive Models: Explore, Explain, and Debug
- [dataviz](https://github.com/clauswilke/dataviz) - A book covering the fundamentals of data visualization.
- [BDA_R_demos](https://github.com/avehtari/BDA_R_demos) - Bayesian Data Analysis demos for R
- [blog](https://github.com/stappit/blog) - I often post solutions to textbook exercises, including: Bayesian Data Analysis (BDA) by Gelman et al; Causal Inference in Statistics Primer (CISP) by Pearl et al; Purely Functional Data Structures (PFDS) by Okasaki.
- [EC525S19](https://github.com/edrubin/EC525S19) -
- [ggplot_flipbook](https://github.com/EvaMaeRey/ggplot_flipbook) - This is a flipbook that builds up plots with ggplot2.
- [r-admin-2018](https://github.com/nwstephens/r-admin-2018) - The R Admin is rad: A guide to professional R tooling and integration
- [aml-training](https://github.com/tidymodels/aml-training) - The most recent version of the Applied Machine Learning notes
- [rstudio-conf-2019](https://github.com/topepo/rstudio-conf-2019) - Slide, code and data for "Applied Machine Learning" at Rstudio-conf 2019
- [the-r-in-spark](https://github.com/r-spark/the-r-in-spark) - Mastering Apache Spark with R
- [tensorflow-w-r](https://github.com/sol-eng/tensorflow-w-r) - TensorFlow with R
- [hrbrmstrs-old-gists](https://github.com/hrbrmstr/hrbrmstrs-old-gists) - ๐๐ All of my old gists in one place
- [splitstackshape](https://github.com/mrdwab/splitstackshape) - R functions to split concatenated data, conveniently stack columns of data.frames, and conveniently reshape data.frames.
- [FES](https://github.com/topepo/FES) - Code and Resources for "Feature Engineering and Selection: A Practical Approach for Predictive Models" by Kuhn and Johnson
- [stat-learning](https://github.com/asadoughi/stat-learning) - Notes and exercise attempts for "An Introduction to Statistical Learning"
- [teach-ML-CEU-master-bizanalytics](https://github.com/szilard/teach-ML-CEU-master-bizanalytics) - Machine Learning #1 and #2 courses at CEU Master of Science in Business Analytics
- [GBM-perf](https://github.com/szilard/GBM-perf) - Performance of various open source GBM implementations
- [bugs-examples-in-stan](https://github.com/jrnold/bugs-examples-in-stan) - Simon Jackman's "BUGS Examples" translated into Stan
- [validate](https://github.com/data-cleaning/validate) - Professional data validation for the R environment
- [seats](https://github.com/idalab-de/seats) - For our new office, we treated the seat assignment as an integer programming problem in R. Conceived and engineered by https://github.com/kirel
- [prezident2018](https://github.com/mpenkov/prezident2018) - Scrape izbirkom.ru for election results, perform some basic exploratory data analysis
- [wassa](https://github.com/noamross/wassa) - WebAssembly Stochastic Simulation Algorithm, OR Adventures in Polyglot Packaging
- [rstudio-conf](https://github.com/rstudio/rstudio-conf) - Materials for rstudio::conf
- [flags](https://github.com/oxguy3/flags) - Freely usable country and state flags from around the world
- [flag-icon](https://github.com/stevenrskelton/flag-icon) - Polymer Web Component for SVG and PNG icons of country, state, province and other flags.
- [two-step](https://github.com/WSJ/two-step) - A JavaScript library for best-practice scrollytelling
- [Statistical-Rethinking-Notes](https://github.com/tmastny/Statistical-Rethinking-Notes) -
- [Statistical-Rethinking](https://github.com/rpruim/Statistical-Rethinking) - Materials assembled while teaching from Statistical Rethinking by R McElreath
- [20171023mapwalkDRUG](https://github.com/bhive01/20171023mapwalkDRUG) - Davis R User Group (D-RUG) Talk about Map and Walk family of functions in purrr package from tidyverse
- [chart-doctor](https://github.com/ft-interactive/chart-doctor) - Sample files to accompany the FT's Chart Doctor column
- [r_docker_hello](https://github.com/SymbolixAU/r_docker_hello) - A simple hello world R-docker example
- [Seeing-Theory](https://github.com/seeingtheory/Seeing-Theory) - A visual introduction to probability and statistics.
- [skimr](https://github.com/ropensci/skimr) - A frictionless, pipeable approach to dealing with summary statistics
- [bartMachine](https://github.com/kapelner/bartMachine) - An R-Java Bayesian Additive Regression Trees implementation
- [visualraster](https://github.com/etiennebr/visualraster) - Illustrate some operations of the raster package
- [BigDataRStrata2017](https://github.com/WinVector/BigDataRStrata2017) - All material for "Modeling big data with R, sparklyr, and Apache Spark" Strata Hadoop 2017.
- [example-models](https://github.com/stan-dev/example-models) - Example models for Stan
- [rmdformats](https://github.com/juba/rmdformats) - HTML output formats for RMarkdown documents
- [zmPDSwR](https://github.com/WinVector/zmPDSwR) - Example R scripts and data for "Practical Data Science with R" 1st edition by Nina Zumel and John Mount (Manning Publications)
## Haskell
- [cryptol](https://github.com/GaloisInc/cryptol) - Cryptol: The Language of Cryptography
- [duckling](https://github.com/facebook/duckling) - Language, engine, and tooling for expressing, testing, and evaluating composable language rules on input strings.
## Java
- [iNNE](https://github.com/tharindurb/iNNE) -
- [kafka-streams-machine-learning-examples](https://github.com/kaiwaehner/kafka-streams-machine-learning-examples) - This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.
- [graal](https://github.com/oracle/graal) - GraalVM: Run Programs Faster Anywhere :rocket:
- [fastr](https://github.com/oracle/fastr) - A high-performance implementation of the R programming language, built on GraalVM.
- [incubator-hudi](https://github.com/apache/incubator-hudi) - Upserts And Incremental Processing on Big Data
- [storm-crawler](https://github.com/DigitalPebble/storm-crawler) - Scalable web crawler based on Apache Storm
- [Processing.R](https://github.com/processing-r/Processing.R) - :coffee: :paintbrush: :1234: R Language Mode in Processing, created by @gaocegege, maintained by @jeremydouglass
- [mit-deep-learning-book-pdf](https://github.com/janishar/mit-deep-learning-book-pdf) - MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
## JavaScript
- [actions](https://github.com/r-lib/actions) - GitHub Actions for the R community
- [earth](https://github.com/cambecc/earth) - a project to visualize global weather conditions
- [preact](https://github.com/preactjs/preact) - โ๏ธ Fast 3kB React alternative with the same modern API. Components & Virtual DOM.
- [nodeppt](https://github.com/ksky521/nodeppt) - This is probably the best web presentation tool so far!
- [github-do-not-ban-us](https://github.com/1995parham/github-do-not-ban-us) - GitHub do not ban us from open source world :iran:
- [TidyBlocks](https://github.com/MayaGans/TidyBlocks) - creating a block based coding program for R's Tidyverse
- [cv](https://github.com/spences10/cv) - My online CV using Gatsby
- [sdss-2019](https://github.com/topepo/sdss-2019) - Slides and code for the "Modeling in the Tidyverse" short course on Wednesday, May 29 2019 at SDSS (Symposium on Data Science and Statistics).
- [mdx-observable](https://github.com/alexkrolick/mdx-observable) - Global state for Markdown documents
- [self-decrypting-html-page](https://github.com/derhuerst/self-decrypting-html-page) - Generate a standalone HTML page that decrypts data.
- [gatsby-remark-highlights](https://github.com/amitpatra/gatsby-remark-highlights) - Adds syntax highlighting to code blocks in markdown files using Atom highlights
- [mdx-deck](https://github.com/jxnblk/mdx-deck) - โ ๏ธ React MDX-based presentation decks
- [data-viz-blog](https://github.com/santhoshsoundar/data-viz-blog) - Over Engineered Data Viz Blog
- [gatsby-plugin-robots-txt](https://github.com/mdreizin/gatsby-plugin-robots-txt) - Gatsby plugin that automatically creates robots.txt for your site
- [iodide](https://github.com/iodide-project/iodide) - Literate scientific computing and communication for the web
- [teddy](https://github.com/newamericafoundation/teddy) - ๐ฉ React-based charting and component library for data visualization
- [remark](https://github.com/remarkjs/remark) - Markdown processor powered by plugins part of the @unifiedjs collective
- [brain.js](https://github.com/BrainJS/brain.js) - ๐ค Neural networks in JavaScript
- [styled-tools](https://github.com/diegohaz/styled-tools) - Useful interpolated functions for CSS-in-JS
- [NeuroEvolutionDriver](https://github.com/mitchvoll/NeuroEvolutionDriver) - 2D autonomous car navigation with optimal driving lines through NeuroEvolution
- [json-server](https://github.com/typicode/json-server) - Get a full fake REST API with zero coding in less than 30 seconds (seriously)
- [redux-time](https://github.com/Monadical-SAS/redux-time) - โ High-performance declarative JS animation library for building games, data-viz experiences, and more w/ React, ThreeJS, Inferno, SnabbDOM and others...
- [styled-components](https://github.com/styled-components/styled-components) - Visual primitives for the component age. Use the best bits of ES6 and CSS to style your apps without stress ๐
- [neataptic](https://github.com/wagenaartje/neataptic) - :rocket: Blazing fast neuro-evolution & backpropagation for the browser and Node.js
- [react-epic-spinners](https://github.com/bondz/react-epic-spinners) - Reusable react components for epic-spinners
- [rd3](https://github.com/tibotiber/rd3) - Playground for React & D3.js
- [muze](https://github.com/chartshq/muze) - Composable data visualisation library for web with a data-first approach
- [learning-react-native](https://github.com/bonniee/learning-react-native) - Code samples for the book Learning React Native.
- [gepetto](https://github.com/hrbrmstr/gepetto) - ๐ ScrapingHub Splash-like REST API for Headless Chrome
- [user2018](https://github.com/topepo/user2018) - Slides and code for the 2018 useR! tutorial "Recipes for Data Processing"
- [react-quickly](https://github.com/azat-co/react-quickly) - Source code for React Quickly [Manning, 2017]: Painless Web Apps with React, JSX, Redux, and GraphQL ๐
- [keras-js](https://github.com/transcranial/keras-js) - Run Keras models in the browser, with GPU support using WebGL
- [vsup](https://github.com/uwdata/vsup) - Code for generating Value-Suppressing Uncertainty Palettes for use in D3 charts.
- [incubator-echarts](https://github.com/apache/incubator-echarts) - A powerful, interactive charting and visualization library for browser
- [constructr](https://github.com/sdllc/constructr) - Electron-based R Shell
- [metalsmith](https://github.com/segmentio/metalsmith) - An extremely simple, pluggable static site generator.
- [resume.github.com](https://github.com/resume/resume.github.com) - Resumes generated using the GitHub informations
- [fmin](https://github.com/benfred/fmin) - Unconstrained function minimization in Javascript
- [lions-](https://github.com/warsus/lions-) - lions commentary on unix - webversion
- [ghacks-user.js](https://github.com/ghacksuserjs/ghacks-user.js) - An ongoing comprehensive user.js template for configuring and hardening Firefox privacy, security and anti-fingerprinting
- [muuri](https://github.com/haltu/muuri) - Responsive, sortable, filterable and draggable grid layouts
- [electron-python-example](https://github.com/fyears/electron-python-example) - Electron as GUI of Python Applications
- [Python-GUI-with-electron](https://github.com/keybraker/Python-GUI-with-electron) - A simple example on how to create electron GUIs for python programs
- [mui](https://github.com/muicss/mui) - Lightweight CSS framework
- [BizCharts](https://github.com/alibaba/BizCharts) - Powerful data visualization library based on G2 and React.
- [charts](https://github.com/frappe/charts) - Simple, responsive, modern SVG Charts with zero dependencies
- [sqlpad](https://github.com/rickbergfalk/sqlpad) - Web-based SQL editor run in your own private cloud. Supports MySQL, Postgres, SQL Server, Vertica, Crate, Presto, SAP HANA, and Cassandra
- [electron-react-boilerplate](https://github.com/electron-react-boilerplate/electron-react-boilerplate) - A Foundation for Scalable Cross-Platform Apps
- [orbit-db](https://github.com/orbitdb/orbit-db) - Peer-to-Peer Databases for the Decentralized Web
- [teachable-machine](https://github.com/micahstubbs/teachable-machine) - Explore how machine learning works, live in the browser. No coding required.
- [DropoutUncertaintyDemos](https://github.com/yaringal/DropoutUncertaintyDemos) - What My Deep Model Doesn't Know...
- [dataviz-popstats](https://github.com/unhcr/dataviz-popstats) - Interactive data-visualisation for popstats.unhcr.org landing page
- [docker-nginx-letsencrypt-rstudio](https://github.com/mikkelkrogsholm/docker-nginx-letsencrypt-rstudio) - Dockerized Nginx + Let's Encrypt sample
- [visual-vocabulary](https://github.com/ft-interactive/visual-vocabulary) - Small examples of data driven graphics -- to be used as starting points.
- [histogram_essay](https://github.com/AmeliaMN/histogram_essay) - This repository contains the code powering Exploring Histograms, an interactive essay by Aran Lunzer and Amelia McNamara.
- [Intro_to_spatial_analysis](https://github.com/Nowosad/Intro_to_spatial_analysis) - Intro to spatial analysis in R
- [serverless-backend](https://github.com/jaehyeon-kim/serverless-backend) - Sources to learn serverless event-driven application development - backend
- [dat](https://github.com/datproject/dat) - :floppy_disk: Share & live sync files anywhere via command line
- [PDBF](https://github.com/uds-datalab/PDBF) - PDBF - A Toolkit for Creating Janiform Data Documents
- [traffic-simulation-de](https://github.com/movsim/traffic-simulation-de) - Source code for javascript simulation of website
- [SublimeKnitr](https://github.com/andrewheiss/SublimeKnitr) - Plugin that adds knitr Markdown and LaTeX support in Sublime Text 2 and 3
- [KaTeX](https://github.com/KaTeX/KaTeX) - Fast math typesetting for the web.
## Jupyter Notebook
- [mml-book.github.io](https://github.com/mml-book/mml-book.github.io) - Companion webpage to the book "Mathematics For Machine Learning"
- [DeOldify](https://github.com/jantic/DeOldify) - A Deep Learning based project for colorizing and restoring old images (and video!)
- [introduction_to_ml_with_python](https://github.com/amueller/introduction_to_ml_with_python) - Notebooks and code for the book "Introduction to Machine Learning with Python"
- [Adversarially-Learned-Anomaly-Detection](https://github.com/houssamzenati/Adversarially-Learned-Anomaly-Detection) - ALAD (Proceedings of IEEE ICDM 2018) official code
- [Grokking-Deep-Learning](https://github.com/iamtrask/Grokking-Deep-Learning) - this repository accompanies the book "Grokking Deep Learning"
- [spark-scala-tutorial](https://github.com/deanwampler/spark-scala-tutorial) - A free tutorial for Apache Spark.
- [JustEnoughScalaForSpark](https://github.com/deanwampler/JustEnoughScalaForSpark) - A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.
- [Meetups](https://github.com/DataSciencePortugal/Meetups) - All meetup contents
- [homemade-machine-learning](https://github.com/trekhleb/homemade-machine-learning) - ๐ค Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
- [shap](https://github.com/slundberg/shap) - A unified approach to explain the output of any machine learning model.
- [lucid](https://github.com/tensorflow/lucid) - A collection of infrastructure and tools for research in neural network interpretability.
- [handson-ml](https://github.com/ageron/handson-ml) - A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
- [big-mac-data](https://github.com/TheEconomist/big-mac-data) - Data and methodology for the Big Mac index
- [CLR](https://github.com/bckenstler/CLR) -
- [h2o-tutorials](https://github.com/h2oai/h2o-tutorials) - Tutorials and training material for the H2O Machine Learning Platform
- [probability](https://github.com/tensorflow/probability) - Probabilistic reasoning and statistical analysis in TensorFlow
- [mldl](https://github.com/Avkash/mldl) - Machine Learning and Deep Learning Resources
- [TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples) - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
- [Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras](https://github.com/curiousily/Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras) - iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data
- [Fraud-detection-using-deep-learning](https://github.com/aaxwaz/Fraud-detection-using-deep-learning) -
- [fastai](https://github.com/fastai/fastai) - The fastai deep learning library, plus lessons and tutorials
- [DeepRL-Agents](https://github.com/awjuliani/DeepRL-Agents) - A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
- [Probabilistic-Programming-and-Bayesian-Methods-for-Hackers](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers) - aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
- [DeepNLP-models-Pytorch](https://github.com/DSKSD/DeepNLP-models-Pytorch) - Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
- [PythonDataScienceHandbook](https://github.com/jakevdp/PythonDataScienceHandbook) - Python Data Science Handbook: full text in Jupyter Notebooks
- [SlidesFromTalks](https://github.com/TheGrimmScientist/SlidesFromTalks) - This is a place for me to share the slides I used from past talks given.
- [pydata-book](https://github.com/wesm/pydata-book) - Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
## Lua
- [textSimilarityConvNet](https://github.com/hohoCode/textSimilarityConvNet) - Semantic Similarity Measurement of Texts using Convolutional Neural Networks (He et al., EMNLP 2015)
## Makefile
- [awesome-blogdown](https://github.com/sellorm/awesome-blogdown) - An awesome curated list of blogs built using blogdown
## Others
- [goodies](https://github.com/rsapkf/goodies) - Collection of GitHub repos, blogs and websites to learn cool things
- [Cookbook](https://github.com/andkret/Cookbook) - The Data Engineering Cookbook
- [Data-Science--Cheat-Sheet](https://github.com/abhat222/Data-Science--Cheat-Sheet) - Cheat Sheets
- [pebble-themes](https://github.com/DesiQuintans/pebble-themes) - 'Pebble' is a family of themes for RStudio 1.2.x
- [tlverse](https://github.com/tlverse/tlverse) - โ๏ธ๐ฆ An Umbrella Package for the tlverse: Your One Stop for Targeted Learning in R
- [R-vs.-Python-for-Data-Science](https://github.com/matloff/R-vs.-Python-for-Data-Science) -
- [app-ideas](https://github.com/florinpop17/app-ideas) - A Collection of application ideas which can be used to improve your coding skills.
- [database_connections](https://github.com/davidski/database_connections) - โ๏ธDemonstration code to connect R on MacOS to various database flavors.
- [awesome-kaitai](https://github.com/kaitai-io/awesome-kaitai) - A curated list of Kaitai Struct tools and resources
- [statrethinking_winter2019](https://github.com/rmcelreath/statrethinking_winter2019) - Statistical Rethinking course at MPI-EVA from Dec 2018 through Feb 2019
- [ked](https://github.com/adam-lynch/ked) - The first Corkonian scripting language
- [deep-learning-books](https://github.com/devakar/deep-learning-books) -
- [notable](https://github.com/notable/notable) - The Markdown-based note-taking app that doesn't suck.
- [awesome-styled-components](https://github.com/styled-components/awesome-styled-components) - A curated list of awesome styled-components resources ๐
- [egghead.io_idiomatic_redux_course_notes](https://github.com/tayiorbeii/egghead.io_idiomatic_redux_course_notes) - Notes from Dan Abramov's Idiomatic Redux course on egghead.io
- [egghead.io_redux_course_notes](https://github.com/tayiorbeii/egghead.io_redux_course_notes) - Notes (and partial transcription) of Dan Abramov's Redux course videos on http://egghead.io
- [A-to-Z-Resources-for-Students](https://github.com/dipakkr/A-to-Z-Resources-for-Students) - โ
Curated list of resources for college students
- [Causal-Inference-Mastery](https://github.com/hammadshaikhha/Causal-Inference-Mastery) - Notes and simulations on graduate level causal inference in statistics with applications to social sciences.
- [deeplearning-resources](https://github.com/keralaai/deeplearning-resources) -
- [mercatus-fellowship-readings](https://github.com/danilofreire/mercatus-fellowship-readings) - Assigned readings for the 2016-2017 Mercatus Adam Smith Fellowship Programme
- [awesome-react-components](https://github.com/brillout/awesome-react-components) - Curated List of React Components & Libraries.
- [ISLR](https://github.com/yahwes/ISLR) - Student Solutions to An Introduction to Statistical Learning with Applications in R
- [nlp-datasets](https://github.com/niderhoff/nlp-datasets) - Alphabetical list of free/public domain datasets with text data for use in Natural Language Processing (NLP)
- [ge-iiot-ml-2017workshop](https://github.com/angelabassa/ge-iiot-ml-2017workshop) - Keynote for October 24, 2017 GE Industrial Machine Learning Workshop
- [companies-using-r](https://github.com/ThinkR-open/companies-using-r) - A Curated list of R uses in entreprise
- [brazilian-states-flags](https://github.com/iconolatry/brazilian-states-flags) - Flags of Brazilian States
- [gam-resources](https://github.com/noamross/gam-resources) -
- [awesome-crawler](https://github.com/BruceDone/awesome-crawler) - A collection of awesome web crawler,spider in different languages
- [awesome-dl4nlp](https://github.com/brianspiering/awesome-dl4nlp) - A curated list of awesome Deep Learning for Natural Language Processing resources
- [country-bounding-boxes](https://github.com/sandstrom/country-bounding-boxes) - A list of ISO 3166-1 country codes and their bounding boxes.
- [distritos_policiais-sp](https://github.com/ceciliadolago/distritos_policiais-sp) -
- [git-flight-rules](https://github.com/k88hudson/git-flight-rules) - Flight rules for git
- [docker-why](https://github.com/jennybc/docker-why) - Notes about why an R user would use Docker
- [DockerCheatSheet](https://github.com/eon01/DockerCheatSheet) - ๐ Docker Cheat Sheet ๐
- [datascience-pizza](https://github.com/PizzaDeDados/datascience-pizza) - ๐ Repositรณrio para juntar informaรงรตes sobre materiais de estudo em anรกlise de dados e รกreas afins, empresas que trabalham com dados e dicionรกrio de conceitos
- [learn-regex](https://github.com/ziishaned/learn-regex) - Learn regex the easy way
- [griffon-vm](https://github.com/gtkcyber/griffon-vm) - Griffon Data Science Virtual Machine
- [poliscitoys](https://github.com/leeper/poliscitoys) - Toy datasets for political science methods
- [awesome-brazil-data](https://github.com/juliohm/awesome-brazil-data) - Curated list of Brazilian datasets for anyone interested in studying the country.
- [SpatialPolygons](https://github.com/AmeliaMN/SpatialPolygons) - Materials for 2017 OpenVisConf talk, How Spatial Polygons Shape Our World
- [rpackages](https://github.com/jtleek/rpackages) - R package development - the Leek group way!
- [awesome-public-datasets](https://github.com/awesomedata/awesome-public-datasets) - A topic-centric list of HQ open datasets. PR โโโ
- [ReScience](https://github.com/ReScience/ReScience) - The ReScience journal. Reproducible Science is Good. Replicated Science is better.
## PHP
- [countries](https://github.com/mledoze/countries) - World countries in JSON, CSV, XML and Yaml. Any help is welcome!
## Perl
- [ni](https://github.com/spencertipping/ni) - Say "ni" to data of any size
## PowerShell
- [Quantum](https://github.com/microsoft/Quantum) - Microsoft Quantum Development Kit Samples
## Python
- [jrnl](https://github.com/jrnl-org/jrnl) - Collect your thoughts and notes without leaving the command line.
- [isolation-forest](https://github.com/Divya-Bhargavi/isolation-forest) - Anomaly detection using isolation forest
- [python-sirajnet](https://github.com/paubric/python-sirajnet) - Using deep complicated NLP to turn your text into my text by arbitrarily swapping words for their synonyms /s
- [auto-sklearn](https://github.com/automl/auto-sklearn) - Automated Machine Learning with scikit-learn
- [transformers](https://github.com/huggingface/transformers) - ๐ค Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.
- [anomaly-detection-resources](https://github.com/yzhao062/anomaly-detection-resources) - Anomaly detection related books, papers, videos, and toolboxes
- [nupic](https://github.com/numenta/nupic) - Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.
- [ctrl](https://github.com/salesforce/ctrl) - Conditional Transformer Language Model for Controllable Generation
- [urlwatch](https://github.com/thp/urlwatch) - urlwatch monitors webpages for you
- [public-apis](https://github.com/public-apis/public-apis) - A collective list of free APIs for use in software and web development.
- [nufhe](https://github.com/nucypher/nufhe) - NuCypher fully homomorphic encryption (NuFHE) library implemented in Python
- [vaex](https://github.com/vaexio/vaex) - Out-of-Core DataFrames for Python, visualize and explore big tabular data at a billion rows per second.
- [spacy-course](https://github.com/ines/spacy-course) - ๐ฉโ๐ซ Advanced NLP with spaCy: A free online course
- [radian](https://github.com/randy3k/radian) - A 21 century R console
- [datasets](https://github.com/tensorflow/datasets) - A collection of datasets ready to use with TensorFlow
- [model-analysis](https://github.com/tensorflow/model-analysis) - Model analysis tools for TensorFlow
- [Pyfhel](https://github.com/ibarrond/Pyfhel) - PYthon For Homomorphic Encryption Libraries, perform encrypted computations such as sum, mult, scalar product or matrix multiplication in Python, with NumPy compatibility. Uses SEAL/HElib/PALISADE as backends, implemented using Cython.
- [ludwig](https://github.com/uber/ludwig) - Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.
- [Efficient-GAN-Anomaly-Detection](https://github.com/houssamzenati/Efficient-GAN-Anomaly-Detection) -
- [Repo-2017](https://github.com/RubensZimbres/Repo-2017) - Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano
- [transform](https://github.com/tensorflow/transform) - Input pipeline framework
- [PFA_Examples](https://github.com/AlpineNow/PFA_Examples) - Examples of PFA scoring engines
- [metropolis-hastings-gans](https://github.com/uber-research/metropolis-hastings-gans) -
- [petastorm](https://github.com/uber/petastorm) - Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
- [lore](https://github.com/instacart/lore) - Lore makes machine learning approachable for Software Engineers and maintainable for Machine Learning Researchers
- [adanet](https://github.com/tensorflow/adanet) - Fast and flexible AutoML with learning guarantees.
- [PyGrid](https://github.com/OpenMined/PyGrid) - A Peer-to-peer Platform for Secure, Privacy-preserving, Decentralized Data Science
- [examples](https://github.com/pytorch/examples) - A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
- [markovify](https://github.com/jsvine/markovify) - A simple, extensible Markov chain generator.
- [youtube-dl](https://github.com/ytdl-org/youtube-dl) - Command-line program to download videos from YouTube.com and other video sites
- [benchm-dl](https://github.com/szilard/benchm-dl) - Playing with various deep learning tools and network architectures
- [DeepLearn](https://github.com/GauravBh1010tt/DeepLearn) - Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.
- [data_visualization](https://github.com/aaronpenne/data_visualization) - A collection of my data visualizations, mostly in Python.
- [twitter_scraping](https://github.com/bpb27/twitter_scraping) - Grab all a user's tweets (and get past 3200 limit)
- [data_utilities](https://github.com/fmv1992/data_utilities) - Data utilities library focused on machine learning and data analysis.
- [stack-lstm-ner](https://github.com/tianlinyang/stack-lstm-ner) - Transition-based NER system
- [DeepPavlov](https://github.com/deepmipt/DeepPavlov) - An open source library for deep learning end-to-end dialog systems and chatbots.
- [eywa](https://github.com/farizrahman4u/eywa) - Open source framework for building conversational agents [WIP]
- [PySyft](https://github.com/OpenMined/PySyft) - A library for encrypted, privacy preserving machine learning
- [credit-card-fraud](https://github.com/ellisvalentiner/credit-card-fraud) - Analysis of credit card fraud data
- [MIDAS](https://github.com/Oracen/MIDAS) - Multiple imputation utilising denoising autoencoder for approximate Bayesian inference
- [keras-rl](https://github.com/keras-rl/keras-rl) - Deep Reinforcement Learning for Keras.
- [hosts](https://github.com/StevenBlack/hosts) - Extending and consolidating hosts files from several well-curated sources like adaway.org, mvps.org, malwaredomainlist.com, someonewhocares.org, and potentially others. You can optionally invoke extensions to block additional sites by category.
- [MAgent](https://github.com/geek-ai/MAgent) - A Platform for Many-agent Reinforcement Learning
- [pytube](https://github.com/nficano/pytube) - A lightweight, dependency-free Python library (and command-line utility) for downloading YouTube Videos.
- [wttr.in](https://github.com/chubin/wttr.in) - :partly_sunny: The right way to check the weather
- [deepwalk](https://github.com/phanein/deepwalk) - DeepWalk - Deep Learning for Graphs
- [awesome-python](https://github.com/vinta/awesome-python) - A curated list of awesome Python frameworks, libraries, software and resources
- [umap](https://github.com/lmcinnes/umap) - Uniform Manifold Approximation and Projection
- [tensorforce](https://github.com/tensorforce/tensorforce) - Tensorforce: a TensorFlow library for applied reinforcement learning
- [gym](https://github.com/openai/gym) - A toolkit for developing and comparing reinforcement learning algorithms.
- [imitation](https://github.com/openai/imitation) - Code for the paper "Generative Adversarial Imitation Learning"
- [num2words](https://github.com/savoirfairelinux/num2words) - Modules to convert numbers to words. 42 --> forty-two
- [zhusuan](https://github.com/thu-ml/zhusuan) - A library for Bayesian deep learning, generative models, based on Tensorflow
- [Stein-Variational-Gradient-Descent](https://github.com/dilinwang820/Stein-Variational-Gradient-Descent) - code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
- [evostra](https://github.com/alirezamika/evostra) - A fast Evolution Strategy implementation in Python
- [jusText](https://github.com/miso-belica/jusText) - Heuristic based boilerplate removal tool
- [untwist](https://github.com/IoSR-Surrey/untwist) -
- [proficiency-metric](https://github.com/DeloitteHux/proficiency-metric) -
- [treecat](https://github.com/posterior/treecat) - A Bayesian latent tree model of high-dimensional heterogeneous data
- [Doubly-Stochastic-DGP](https://github.com/ICL-SML/Doubly-Stochastic-DGP) - Deep Gaussian Processes with Doubly Stochastic Variational Inference
- [stanford-tensorflow-tutorials](https://github.com/chiphuyen/stanford-tensorflow-tutorials) - This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
- [tpot](https://github.com/EpistasisLab/tpot) - A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
- [dynamic-nmf](https://github.com/derekgreene/dynamic-nmf) - Dynamic Topic Modeling via Non-negative Matrix Factorization
- [Dictionaries](https://github.com/titoBouzout/Dictionaries) - Hunspell UTF8 dictionaries. These work with Sublime Text. [Spell check]
- [onionshare](https://github.com/micahflee/onionshare) - Securely and anonymously send and receive files, and publish onion sites
## QML
- [gedotmap](https://github.com/PaulC91/gedotmap) - GE 2015/17 + EU Ref voter density shiny app
## R
- [ctv-AnomalyDetection](https://github.com/pridiltal/ctv-AnomalyDetection) - CRAN Task View: Anomaly Detection with R ๐๐๐๐๐๐๐๐๐๐๐๐๐๐๏ธ๐๐
- [dance](https://github.com/romainfrancois/dance) - tibble() dancing ๐
- [rap](https://github.com/romainfrancois/rap) - yet another experimental way of processing a data.frame rowwisely
- [distill](https://github.com/rstudio/distill) - Distill for R Markdown
- [dipsaus](https://github.com/dipterix/dipsaus) - Dev repo for R package dipsaus
- [capsule](https://github.com/MilesMcBain/capsule) - An inversion of renv for low effort reproducible R package libraries
- [generativeart](https://github.com/cutterkom/generativeart) - Create Generative Art with R
- [asciicast](https://github.com/r-lib/asciicast) - Turn R scripts into terminal screencasts
- [mockery](https://github.com/r-lib/mockery) - A mocking library for R.
- [dbtest](https://github.com/jonkeane/dbtest) - dbtest: A Test Environment for DB Queries in R
- [codefolder](https://github.com/ijlyttle/codefolder) - Enable per-page code-folding for Bookdown and Distill
- [rmote](https://github.com/cloudyr/rmote) - Utilities for running R on a remote server
- [tidygeocoder](https://github.com/jessecambon/tidygeocoder) - A tidyverse-style geocoder interface for R
- [ochRe](https://github.com/ropenscilabs/ochRe) - Australia-themed Colour Palettes
- [themis](https://github.com/EmilHvitfeldt/themis) - Extra recipes steps for dealing with unbalanced data
- [ggeffects](https://github.com/strengejacke/ggeffects) - Tidy Data Frames of Marginal Effects for ggplot2
- [checkmate](https://github.com/mllg/checkmate) - Fast and versatile argument checks
- [tidyfast](https://github.com/TysonStanley/tidyfast) - Fast and efficient alternatives to tidyr functions built on data.table #rdatatable #rstats
- [hans_rosling_bubble](https://github.com/keithmcnulty/hans_rosling_bubble) - Create Hans Rosling bubble chart in one command in R
- [orderly](https://github.com/vimc/orderly) - :hospital::ambulance: Lightweight Reproducible Reporting for R
- [htmlent](https://github.com/tjmahr/htmlent) - Package to make HTML entities available to RStudio's autocompletion
- [rmdTemplates](https://github.com/Pakillo/rmdTemplates) - R package containing a collection of Rmarkdown templates
- [rtemis](https://github.com/egenn/rtemis) - Advanced Machine Learning and Visualization
- [vtree](https://github.com/nbarrowman/vtree) - An R package for calculating and drawing variable trees
- [fuzzyjoin](https://github.com/dgrtwo/fuzzyjoin) - Join tables together on inexact matching
- [ckanr](https://github.com/ropensci/ckanr) - R client for the CKAN API
- [forecastML](https://github.com/nredell/forecastML) - An R package for multi-step-ahead direct forecasting with standard machine learning algorithms
- [signs](https://github.com/BenjaminWolfe/signs) - Insert Proper Minus Signs
- [fastpipe](https://github.com/moodymudskipper/fastpipe) - A fast pipe implementation
- [rco](https://github.com/jcrodriguez1989/rco) - The R Code Optimizer
- [santoku](https://github.com/hughjonesd/santoku) - A versatile cutting tool for R
- [almanac](https://github.com/DavisVaughan/almanac) - The Grammar of Schedules
- [fishualize](https://github.com/nschiett/fishualize) - The fishualize package provides color scales for plotting in R based on natureโs most stunning and colorful organisms: teleost fishes (with a few chondrichthyan cameos).
- [xfun](https://github.com/yihui/xfun) - Yihui Xie's miscellaneous R functions
- [pivotable](https://github.com/edgararuiz/pivotable) -
- [funModeling](https://github.com/pablo14/funModeling) - R package: funModeling: data cleaning, importance variable analysis and model perfomance
- [dm](https://github.com/krlmlr/dm) - Relational data models
- [fwiffer](https://github.com/gadenbuie/fwiffer) - ๐โจ Fixed width file definitions made easy
- [multiverse](https://github.com/javierluraschi/multiverse) - A set of packages to scale data science workflows
- [mixtape](https://github.com/johnson-shuffle/mixtape) - Data for Causal Inference: The Mixtape by Scott Cunningham
- [pins](https://github.com/rstudio/pins) - Pin, Discover and Share Resources
- [webutils](https://github.com/jeroen/webutils) - Utility functions for web applications
- [plumbpkg](https://github.com/sol-eng/plumbpkg) - Example R package that includes Plumber APIs
- [pet-names](https://github.com/nolis-llc/pet-names) - Generating pet names - creating an R Keras model and deploying it in a Docker container
- [scattermore](https://github.com/exaexa/scattermore) - very fast scatterplots for R
- [ggrastr](https://github.com/VPetukhov/ggrastr) - Raster geoms for ggplot2
- [blog](https://github.com/statsonthecloud/blog) - A repository for code related to the blog
- [sparkxgb](https://github.com/rstudio/sparkxgb) - R interface for XGBoost on Spark
- [feasts](https://github.com/tidyverts/feasts) - Feature Extraction And Statistics for Time Series
- [CVXR](https://github.com/cvxgrp/CVXR) - An R modeling language for convex optimization problems.
- [gglayer](https://github.com/GuangchuangYu/gglayer) - provide extra layers for ggplot2
- [tweetrbot](https://github.com/statnmap/tweetrbot) - Functions for a Twitter bot
- [polite](https://github.com/dmi3kno/polite) - Be nice on the web
- [ggpointdensity](https://github.com/LKremer/ggpointdensity) - :chart_with_upwards_trend: :bar_chart: Introduces geom_pointdensity(): A Cross Between a Scatter Plot and a 2D Density Plot.
- [favoriteRpackages](https://github.com/abichat/favoriteRpackages) - My favorite R packages
- [importedPackageTimings](https://github.com/rmflight/importedPackageTimings) - Time combinations of loading packages
- [mlapi](https://github.com/dselivanov/mlapi) - Machine learning in R that doesnโt suck
- [unglue](https://github.com/moodymudskipper/unglue) - Extract matched substrings using a pattern, similar to what package glue does in reverse
- [ratlas](https://github.com/atlas-aai/ratlas) - Custom graphics and report generation for @atlas-aai
- [rcorpora](https://github.com/gaborcsardi/rcorpora) - R package with a collection of small corpuses of interesting data, from https://github.com/dariusk/corpora
- [languageserver](https://github.com/REditorSupport/languageserver) - An implementation of the Language Server Protocol for R
- [ingredients](https://github.com/ModelOriented/ingredients) - Model ingredients - model level feature effects and feature importance
- [DrWhy](https://github.com/ModelOriented/DrWhy) - DrWhy is the collection of tools for Explainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.
- [slide](https://github.com/DavisVaughan/slide) - Sliding Window Functions
- [mlr3](https://github.com/mlr-org/mlr3) - mlr3: Machine Learning in R - next generation
- [The-Elements-Of-Statistical-Learning](https://github.com/mmarouen/The-Elements-Of-Statistical-Learning) - This repository contains R code for exercices and plots in the famous book.
- [roxytest](https://github.com/mikldk/roxytest) - Inline testthat tests with roxygen2
- [ggtextures](https://github.com/clauswilke/ggtextures) - Drawing textured rectangles and bars with ggplot
- [multiscales](https://github.com/clauswilke/multiscales) - Multivariate scales for ggplot2
- [ggtext](https://github.com/clauswilke/ggtext) - Improved text rendering for ggplot2.
- [simMixedDAG](https://github.com/IyarLin/simMixedDAG) - The simMixedDAG package enables simulation of "real life" datasets from DAGs
- [strapgod](https://github.com/DavisVaughan/strapgod) - "I'm beginning to feel like a strap god." - Eminem
- [disk.frame](https://github.com/xiaodaigh/disk.frame) - Fast Disk-Based Parallelized Data Manipulation Framework for Larger-than-RAM Data
- [renv](https://github.com/rstudio/renv) - renv: Project environments for R.
- [armacmp](https://github.com/dirkschumacher/armacmp) - ๐ Automatically compile linear algebra R code to C++ with Armadillo
- [DesktopDeployR](https://github.com/wleepang/DesktopDeployR) - A framework for deploying self-contained R-based applications to the desktop
- [easystats](https://github.com/easystats/easystats) - :milky_way: The easyverse
- [NineteenEightyR](https://github.com/m-clark/NineteenEightyR) - :sunrise_over_mountains: :vhs: like totally rad
- [modeldb](https://github.com/tidymodels/modeldb) - Run models inside a database using R
- [progressr](https://github.com/HenrikBengtsson/progressr) - ไธ R package: A Unifying API for Progress Updates [EXPERIMENTAL]
- [stfs](https://github.com/mdedge/stfs) - Code and supplemental material for Statistical Thinking from Scratch
- [ggeconodist](https://github.com/hrbrmstr/ggeconodist) - ๐ Create Diminutive Distribution Charts
- [rscodeio](https://github.com/anthonynorth/rscodeio) - An RStudio theme inspired by Visual Studio Code.
- [ggwrap](https://github.com/wilkox/ggwrap) - ๐ฏ Wrap ggplot2 plots over multiple rows
- [equatiomatic](https://github.com/datalorax/equatiomatic) - Convert models to LaTeX equations
- [ggfittext](https://github.com/wilkox/ggfittext) - ๐ ggplot2 geoms to fit text into boxes
- [ethercalc](https://github.com/hrbrmstr/ethercalc) - ๐งฎOrchestrate and Exchange Data with 'EtherCalc' Instances
- [brms](https://github.com/paul-buerkner/brms) - brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
- [unitscales](https://github.com/EmilHvitfeldt/unitscales) - Adding additional ggplot2 scales that adds units
- [iBreakDown](https://github.com/ModelOriented/iBreakDown) - Break down ML model predictions with variable attribution (LIME, SHAP, BreakDown)
- [inspectdf](https://github.com/alastairrushworth/inspectdf) - ๐๐Tools for Exploring and Comparing Data Frames
- [purrrogress](https://github.com/halpo/purrrogress) - Add progress bars to mapping functions
- [tinytest](https://github.com/markvanderloo/tinytest) - A lightweight, no-dependency, but full-featured package for unit testing in R
- [panelr](https://github.com/jacob-long/panelr) - Regression models and utilities for repeated measures and panel data
- [tidycode](https://github.com/LucyMcGowan/tidycode) -
- [matahari](https://github.com/jhudsl/matahari) - ๐ I Spy With My Little Eye
- [rstatix](https://github.com/kassambara/rstatix) - Pipe-friendly Framework for Basic Statistical Tests in R
- [pre](https://github.com/marjoleinF/pre) - an R package for deriving Prediction Rule Ensembles
- [modules](https://github.com/klmr/modules) - An alternative module system for R
- [tvthemes](https://github.com/Ryo-N7/tvthemes) - ggplot2 themes and palettes based on your favorite TV shows
- [distributions3](https://github.com/alexpghayes/distributions3) - Probability Distributions as S3 Objects
- [tradestatistics](https://github.com/ropensci/tradestatistics) - R package to access Open Trade Statistics API
- [Advanced-R-Solutions](https://github.com/Tazinho/Advanced-R-Solutions) - Set of solutions for the Advanced R programming book
- [sergeant](https://github.com/hrbrmstr/sergeant) - :guardsman: Tools to Transform and Query Data with 'Apache' 'Drill'
- [htmlunit](https://github.com/hrbrmstr/htmlunit) - ๐ธ๐งฐโ๏ธTools to Scrape Dynamic Web Content via the 'HtmlUnit' Java Library
- [lindia](https://github.com/yeukyul/lindia) - Extension package of linear regression diagonostic plots in ggplot2.
- [safejoin](https://github.com/moodymudskipper/safejoin) - Wrappers around dplyr functions to join safely using various checks
- [riskmetric](https://github.com/pharmaR/riskmetric) - Metrics to evaluate the risk of R packages
- [tidylog](https://github.com/elbersb/tidylog) - Tidylog provides feedback about basic dplyr operations. It provides simple wrapper functions for the most common functions, such as filter, mutate, select, and group_by.
- [outsider](https://github.com/AntonelliLab/outsider) - :black_square_button::registered: Install and run programs, outside of R, inside of R
- [debugme](https://github.com/r-lib/debugme) - Easy and efficient debugging for R packages
- [hardhat](https://github.com/tidymodels/hardhat) - A Toolkit for the Construction of Modeling Packages
- [vapoRwave](https://github.com/moldach/vapoRwave) - ๐ผ๐พ๐นVaporwave themes and color palettes for ggplot2๐พ๐จโ๐ค๐บ
- [tidyroc](https://github.com/dariyasydykova/tidyroc) -
- [awesome-network-analysis](https://github.com/briatte/awesome-network-analysis) - A curated list of awesome network analysis resources.
- [ggshapes](https://github.com/EmilHvitfeldt/ggshapes) - Adding various geometrical shapes to ggplot2
- [openscoring-r](https://github.com/openscoring/openscoring-r) - R client library for the Openscoring REST web service
- [isofor](https://github.com/Zelazny7/isofor) - Isolation Forest implementation in R
- [dub](https://github.com/egnha/dub) - Unpacking assignment via pattern matching
- [rong](https://github.com/egnha/rong) - The rong approach to wrong inputs. Two (w)rongs make a right.
- [gestalt](https://github.com/egnha/gestalt) - Tidy Tools for Making and Combining Functions
- [nofrills](https://github.com/egnha/nofrills) - Low-cost anonymous functions
- [boilerpipeR](https://github.com/mannau/boilerpipeR) - Interface to the boilerpipe Java library by Christian Kohlschutter (http://code.google.com/p/boilerpipe/)
- [parzer](https://github.com/ropenscilabs/parzer) - Parse lat/lon coordinates
- [forge](https://github.com/rstudio/forge) - forge: Casting values into shape
- [conflr](https://github.com/line/conflr) - Post R Markdown documents to Confluence
- [polyreg](https://github.com/matloff/polyreg) -
- [RPresto](https://github.com/prestodb/RPresto) - DBI-based adapter for Presto for the statistical programming language R.
- [dbplot](https://github.com/edgararuiz/dbplot) - Simplifies plotting of database and sparklyr data
- [reapr](https://github.com/hrbrmstr/reapr) - ๐ธโโน๏ธ Reap Information from Websites
- [ggflags](https://github.com/rensa/ggflags) - A flag geom for ggplot2. Tweaks the original by using round flags (great for plotting as points).
- [xmltools](https://github.com/dantonnoriega/xmltools) - Tools to look at xml data. Has functions similar to the `tree` command line tool ( xml_view_tree). Allows one to find paths quickly, including just terminal node paths (xml_get_paths). Also has two functions for helping convert xml code to data frames (xml_to_df and xml_dig_df).
- [statistical-rethinking](https://github.com/cavaunpeu/statistical-rethinking) - Solutions for the practice problems
- [quickplumb](https://github.com/geotheory/quickplumb) - Generate a highly flexible plumber API with just a few lines
- [ggnewscale](https://github.com/eliocamp/ggnewscale) - Multiple Fill and Color Scales in `ggplot2`
- [MachineShop](https://github.com/brian-j-smith/MachineShop) - MachineShop: R package of models and tools for machine learning
- [gt](https://github.com/rstudio/gt) - Easily generate information-rich, publication-quality tables from R
- [httptest](https://github.com/nealrichardson/httptest) - A Test Environment for HTTP Requests in R
- [safepredict](https://github.com/alexpghayes/safepredict) - Consistent prediction following tidymodels principles
- [leadr](https://github.com/tmastny/leadr) -
- [r-tensorflow-api](https://github.com/tmobile/r-tensorflow-api) - A small Docker container for using R and TensorFlow as an enterprise API
- [defer](https://github.com/lbartnik/defer) -
- [precisely](https://github.com/malcolmbarrett/precisely) - :dart: An R package to estimate sample size based on precision rather than power
- [vizstorm-GIF](https://github.com/USGS-VIZLAB/vizstorm-GIF) -
- [pak](https://github.com/r-lib/pak) - A fresh approach to package installation
- [carrier](https://github.com/r-lib/carrier) - Create standalone functions for remote execution
- [flowery](https://github.com/lionel-/flowery) - Make R a more flowery language with generators and transducers
- [r-hedgehog](https://github.com/hedgehogqa/r-hedgehog) - Release with confidence, state-of-the-art property testing for R.
- [salty](https://github.com/mdlincoln/salty) - Turn Clean Data Into Messy Data
- [homomorpheR](https://github.com/bnaras/homomorpheR) - Homomorphic Computations in R
- [gganatogram](https://github.com/jespermaag/gganatogram) - Create anatograms using ggplot2
- [customLayout](https://github.com/zzawadz/customLayout) - Simple extension of basic layout function from R.
- [chunked](https://github.com/edwindj/chunked) - Chunkwise Text-file Processing for 'dplyr'
- [lobstr](https://github.com/r-lib/lobstr) - Understanding complex R objects with tools similar to str()
- [ungeviz](https://github.com/wilkelab/ungeviz) - Tools for visualizing uncertainty with ggplot2
- [jetpack](https://github.com/ankane/jetpack) - A friendly package manager for R
- [tidymodels](https://github.com/tidymodels/tidymodels) - Easily Install and Load the 'Tidymodels' Packages
- [hexagon](https://github.com/mkearney/hexagon) - โ๏ธโนโถ๏ธ R package for creating hexagon shaped xy data frames.
- [CNNtutorial](https://github.com/monogenea/CNNtutorial) -
- [nyhackr-docker-talk](https://github.com/noamross/nyhackr-docker-talk) - Slides, Code, and Links to Resources from "Docker for the User," delivered at nyhackr 2018-07-11
- [anytime](https://github.com/eddelbuettel/anytime) - Anything to POSIXct or Date Converter
- [modelDown](https://github.com/ModelOriented/modelDown) - modelDown generates a website with HTML summaries for predictive models
- [emperors](https://github.com/zonination/emperors) - Roman Emperors from 26 BC to 395 AD
- [rayshader](https://github.com/tylermorganwall/rayshader) - R Package for 2D and 3D mapping and data visualization
- [rtrek](https://github.com/leonawicz/rtrek) - R package for Star Trek datasets and related R functions.
- [DALEX](https://github.com/ModelOriented/DALEX) - Descriptive mAchine Learning EXplanations
- [webdriver](https://github.com/rstudio/webdriver) - WebDriver client in R
- [shinydashboardPlus](https://github.com/RinteRface/shinydashboardPlus) - extensions for shinydashboard
- [joy-of-fp](https://github.com/hadley/joy-of-fp) - Supplemental materials for "The joy of functional programming"
- [benchm-ml](https://github.com/szilard/benchm-ml) - A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
- [greta.live](https://github.com/goldingn/greta.live) - a repo for playing with ideas around live mcmc traceplots
- [tidyversity](https://github.com/mkearney/tidyversity) - ๐ Tidy tools for academics
- [keras-workshop](https://github.com/MangoTheCat/keras-workshop) - Data and scripts for keras course
- [iml](https://github.com/christophM/iml) - iml: interpretable machine learning R package
- [casewhen](https://github.com/RLesur/casewhen) - Create reusable dplyr::case_when() functions
- [row-oriented-workflows](https://github.com/jennybc/row-oriented-workflows) - Row-oriented workflows in R with the tidyverse
- [caffeR](https://github.com/cnaumzik/caffeR) -
- [randomizr](https://github.com/DeclareDesign/randomizr) - randomizr: Easy-to-Use Tools for Common Forms of Random Assignment and Sampling
- [transformr](https://github.com/thomasp85/transformr) - Smooth Polygon Transformations
- [pearls](https://github.com/thomasp85/pearls) - Operations on Lists of Data Frames
- [stats337](https://github.com/hadley/stats337) - Readings in applied data science
- [ggdag](https://github.com/malcolmbarrett/ggdag) - :arrow_lower_left: :arrow_lower_right: An R package for working with causal directed acyclic graphs (DAGs)
- [decryptr](https://github.com/decryptr/decryptr) - An extensible API for breaking captchas
- [pointblank](https://github.com/rich-iannone/pointblank) - Validation of local and remote data tables
- [vistime](https://github.com/shosaco/vistime) - an R package for pretty timeline creation
- [unpivotr](https://github.com/nacnudus/unpivotr) - Unpivot complex and irregular data layouts in R
- [onehot](https://github.com/Zelazny7/onehot) - Quickly transform data.frames into onehot encoded matrices
- [kv](https://github.com/decisionpatterns/kv) - Key-Value Iteration in R
- [crypto_tracker](https://github.com/PaulC91/crypto_tracker) - shiny app to get personalised metrics on cryptocurrency investments
- [rsparse](https://github.com/dselivanov/rsparse) - Fast and accurate machine learning on sparse matrices - matrix factorizations, regression, classification, top-N recommendations.
- [RestRserve](https://github.com/dselivanov/RestRserve) - [work-in-progress] RestRserve is a R web API framework for building high-performance microservices and app backends
- [reinforcelearn](https://github.com/markusdumke/reinforcelearn) - R Package for Reinforcement Learning
- [MUSA-620-Week-6](https://github.com/MUSA-620-Spring-2018/MUSA-620-Week-6) - Web scraping 1
- [ggpomological](https://github.com/gadenbuie/ggpomological) - ๐ Pomological plot theme for ggplot2
- [sentimentr](https://github.com/trinker/sentimentr) - Dictionary based sentiment analysis that considers valence shifters
- [opencpu](https://github.com/opencpu/opencpu) - OpenCPU system for embedded scientific computation and reproducible research
- [om_skeleton](https://github.com/open-meta/om_skeleton) - This is a public, reusable skeleton for building multi-page, multi-user web sites with authentication. Based on R and Shiny.
- [mandalas](https://github.com/aschinchon/mandalas) - Mandalas in R
- [ShinySky](https://github.com/AnalytixWare/ShinySky) - Various UI widgets/components not part of Shiny e.g. alerts, styled buttons
- [future.callr](https://github.com/HenrikBengtsson/future.callr) - :rocket: R package future.callr: A Future API for Parallel Processing using 'callr'
- [sensemakr](https://github.com/chadhazlett/sensemakr) - Sensitivity Analysis
- [deidentifyr](https://github.com/wilkox/deidentifyr) - ๐ฅ An R package for deidentifying datasets that may contain personally identifiable information (PII)
- [provisionr](https://github.com/mrc-ide/provisionr) - :package::package::arrow_right::classical_building: Provision a library of R packages
- [drake](https://github.com/ropensci/drake) - An R-focused pipeline toolkit for reproducibility and high-performance computing
- [searcher](https://github.com/r-assist/searcher) - Query Search Portals from R
- [profmem](https://github.com/HenrikBengtsson/profmem) - ๐ง R package: profmem - Simple Memory Profiling for R
- [yuck](https://github.com/tpq/yuck) - An R package to add something like list comprehensions to for-loops in R
- [kerasformula](https://github.com/rdrr1990/kerasformula) - A high-level interface to keras for R that takes advantage of formulas
- [gendeR](https://github.com/ciflikli/gendeR) - LSE IR Gender Project
- [shades](https://github.com/jonclayden/shades) - Simple colour manipulation in R
- [sugrrants](https://github.com/earowang/sugrrants) - SUpporting GRaphics with R for ANalysing Time Series
- [gretchenalbrecht](https://github.com/dicook/gretchenalbrecht) -
- [patchwork](https://github.com/thomasp85/patchwork) - The Composer of ggplots
- [docopt.R](https://github.com/docopt/docopt.R) - Command-line interface description language for R (http://docopt.org)
- [Commute_Data](https://github.com/mgsosna/Commute_Data) - Visualizations of my daily commute
- [Rokemon](https://github.com/schochastics/Rokemon) - Pokemon themed R package
- [Rcrawler](https://github.com/salimk/Rcrawler) - An R web crawler and scraper
- [clear-water](https://github.com/Chicago/clear-water) - Forecasting elevated levels of E. coli at Chicago beaches to provide proper warning to beach-goers.
- [xgboostExplainer](https://github.com/AppliedDataSciencePartners/xgboostExplainer) - An R package that makes xgboost models fully interpretable
- [lockbox](https://github.com/robertzk/lockbox) - Bundler-style dependency management for R
- [brazilmaps](https://github.com/rpradosiqueira/brazilmaps) - A R package with different geographic levels of brazilian maps
- [jsReact](https://github.com/kcf-jackson/jsReact) - R package: Modelling in R. Interactivity in JS. Best of both worlds.
- [SOfun](https://github.com/mrdwab/SOfun) - Functions I've written as answers to R questions on Stack Overflow
- [ggphysics](https://github.com/chang/ggphysics) - Physics animations in ggplot2, just for fun.
- [statisticalModeling](https://github.com/dtkaplan/statisticalModeling) -
- [UpSetR](https://github.com/hms-dbmi/UpSetR) - An R implementation of the UpSet set visualization technique published by Lex, Gehlenborg, et al..
- [Rpostal](https://github.com/Datactuariat/Rpostal) - R bindings to libpostal for fast international address parsing/normalization
- [tidybayes](https://github.com/mjskay/tidybayes) - Bayesian analysis + tidy data + geoms (R package)
- [geocompr](https://github.com/Robinlovelace/geocompr) - Open source book: Geocomputation with R
- [PolData](https://github.com/erikgahner/PolData) - A dataset with political datasets
- [async](https://github.com/r-lib/async) - Asynchronous HTTP requests in R -- UNDER CONSTRUCTION
- [textnets](https://github.com/cbail/textnets) - R package to perform automated text analysis using network techniques
- [tsibble](https://github.com/tidyverts/tsibble) - Tidy Temporal Data Frames and Tools
- [reconstructr](https://github.com/Ironholds/reconstructr) - Tidy tools for session reconstruction and analysis
- [rethinking](https://github.com/rmcelreath/rethinking) - Statistical Rethinking course and book package
- [rmonad](https://github.com/arendsee/rmonad) - Pipelines you can compute on
- [linemap](https://github.com/rCarto/linemap) - :aquarius: Create maps made of lines
- [jericho](https://github.com/hrbrmstr/jericho) - :notebook_with_decorative_cover: Extract plain or structured text from HTML content in R
- [cleanNLP](https://github.com/statsmaths/cleanNLP) - R package providing annotators and a normalized data model for natural language processing
- [ggquiver](https://github.com/mitchelloharawild/ggquiver) - R package for quiver plots in 'ggplot2'
- [text2vec](https://github.com/dselivanov/text2vec) - Fast vectorization, topic modeling, distances and GloVe word embeddings in R.
- [fiery](https://github.com/thomasp85/fiery) - A flexible and lightweight web server
- [routr](https://github.com/thomasp85/routr) - Routing of Web Requests in R
- [ISL](https://github.com/ilyakava/ISL) - Student Sourced Solution Manual for "An Introduction to Statistical Learning: with Applications in R"
- [Elements-of-Statistical-Learning](https://github.com/ajtulloch/Elements-of-Statistical-Learning) - Contains LaTeX, SciPy and R code providing solutions to exercises in Elements of Statistical Learning (Hastie, Tibshirani & Friedman)
- [Shiny-Demos](https://github.com/EconometricsBySimulation/Shiny-Demos) - In this repo I will keep various experiments using Shiny
- [containerit](https://github.com/o2r-project/containerit) - Package an R workspace and all dependencies as a Docker container
- [RoogleVision](https://github.com/cloudyr/RoogleVision) - R Package for Image Recognition using Google Cloud Vision
- [reqres](https://github.com/thomasp85/reqres) - Powerful classes for http requests and responses
- [beyond-single-core-R](https://github.com/ljdursi/beyond-single-core-R) - Short tour of parallel and foreach packages, and how to think about scaling data analyses
- [nseval](https://github.com/crowding/nseval) - The missing API for non-standard evaluation and metaprogramming in R
- [billboarder](https://github.com/dreamRs/billboarder) - :bar_chart: R Htmlwidget for billboard.js
- [ggplot_theme_Publication](https://github.com/koundy/ggplot_theme_Publication) -
- [rpivotTable](https://github.com/smartinsightsfromdata/rpivotTable) - A R wrapper for the great library pivottable
- [repurrrsive](https://github.com/jennybc/repurrrsive) - Recursive lists to use in teaching and examples, because there is no iris data for lists.
- [wooldridge](https://github.com/JustinMShea/wooldridge) - The official R data package for "Introductory Econometrics: A Modern Approach". A vignette contains example models from each chapter.
- [greta.gam](https://github.com/greta-dev/greta.gam) - a greta extension for generalised additive modelling using mgcv
- [urban_R_theme](https://github.com/UrbanInstitute/urban_R_theme) - NOTE: urban_R_theme is being phased out. Please use library(urbnthemes).
- [ggstance](https://github.com/lionel-/ggstance) - Horizontal ggplot2 components
- [cutpointr](https://github.com/Thie1e/cutpointr) - Optimal cutpoints in R: determining and validating optimal cutpoints in binary classification
- [naniar](https://github.com/njtierney/naniar) - Tidy data structures, summaries, and visualisations for missing data
- [ggpubr](https://github.com/kassambara/ggpubr) - 'ggplot2' Based Publication Ready Plots
- [vadr](https://github.com/crowding/vadr) - Making R a better language
- [ggsn](https://github.com/oswaldosantos/ggsn) - R package to add north symbols and scale bars to maps created with ggplot or ggmap
- [heatbarWithRHighcharts](https://github.com/d-qn/heatbarWithRHighcharts) - Interactive heatmap-barchat with R/highcharts
- [osmplotr](https://github.com/ropensci/osmplotr) - Data visualisation using OpenStreetMap objects
- [circlize](https://github.com/jokergoo/circlize) - Circular visualization in R
- [docstring](https://github.com/Dasonk/docstring) - Provides docstring like functionality to R functions without requiring the need to create a package.
- [timetk](https://github.com/business-science/timetk) - A toolkit for working with time series in R
- [request](https://github.com/sckott/request) - http requests DSL for R
- [tmap](https://github.com/mtennekes/tmap) - R package for thematic maps
- [rdom](https://github.com/cpsievert/rdom) - Render and parse dynamic web pages from R
- [software-review](https://github.com/ropensci/software-review) - rOpenSci Software Peer Review of community-contributed packages
- [geofacet](https://github.com/hafen/geofacet) - R package for geographical faceting with ggplot2
- [brmap](https://github.com/italocegatta/brmap) - Polรญgonos de unidades territoriais do Brasil em R Simple Feature
- [Rbitcoin](https://github.com/jangorecki/Rbitcoin) - R & bitcoin integration
- [pdp](https://github.com/bgreenwell/pdp) - A general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.
- [olsrr](https://github.com/rsquaredacademy/olsrr) - Tools for developing linear regression models
- [datasauRus](https://github.com/lockedata/datasauRus) - R Package ๐ฆ Containing the Datasaurus Dozen datasets :bar_chart:
- [greta](https://github.com/greta-dev/greta) - simple and scalable statistical modelling in R
- [stan-statespace](https://github.com/sinhrks/stan-statespace) - Stan models for state space time series
- [nowcasting_in_stan](https://github.com/khakieconomics/nowcasting_in_stan) - Simple demonstration of nowcasting in stan
- [openxlsx](https://github.com/awalker89/openxlsx) - R package for .xlsx file reading and writing.
- [sourcesans](https://github.com/kjhealy/sourcesans) -
- [ggparliament](https://github.com/RobWHickman/ggparliament) - Simple parliament plots using ggplot2
- [ggspatial](https://github.com/paleolimbot/ggspatial) - Enhancing spatial visualization in ggplot2
- [standardize](https://github.com/CDEager/standardize) - Tools for Standardizing Variables for Regression in R
- [remake](https://github.com/hadley/remake) - Make-like declarative workflows in R
- [prediction](https://github.com/leeper/prediction) - Tidy, Type-Safe 'prediction()' Methods
- [numform](https://github.com/trinker/numform) - tools to assist in the formatting of numbers and plots for publication
- [cognizer](https://github.com/ColumbusCollaboratory/cognizer) - R package to call IBM Watson services.
- [hexSticker](https://github.com/GuangchuangYu/hexSticker) - :sparkles: Hexagon sticker in R
- [DiagrammeR](https://github.com/rich-iannone/DiagrammeR) - Graph and network visualization using tabular data in R.
- [mathpix](https://github.com/jonocarroll/mathpix) - Query the mathpix API to convert math images to LaTeX
- [tidygraph](https://github.com/thomasp85/tidygraph) - A tidy API for graph manipulation
- [monkeylearn](https://github.com/ropensci/monkeylearn) - :monkey: R package for text analysis with Monkeylearn :monkey:
- [CausalImpact](https://github.com/google/CausalImpact) - An R package for causal inference in time series
- [bayesplot](https://github.com/stan-dev/bayesplot) - bayesplot R package for plotting Bayesian models
- [ggraph](https://github.com/thomasp85/ggraph) - Grammar of Graph Graphics
- [textmining_southpark](https://github.com/walkerkq/textmining_southpark) - http://kaylinpavlik.com/text-mining-south-park/
- [findviews](https://github.com/tsellam/findviews) - A view generator for multivariate data
- [janitor](https://github.com/sfirke/janitor) - simple tools for data cleaning in R
- [rho](https://github.com/rho-devel/rho) -
- [asdfree](https://github.com/ajdamico/asdfree) - analyze survey data for free
- [giphyr](https://github.com/haozhu233/giphyr) - A R package for giphy API
- [r-gotchas](https://github.com/mikelove/r-gotchas) - R gotchas
- [LaplacesDemon](https://github.com/LaplacesDemonR/LaplacesDemon) - A complete environment for Bayesian inference within R
- [dart-throwing-chimp](https://github.com/ulfelder/dart-throwing-chimp) - Code and data for selected posts on my Dart-Throwing Chimp blog and other work on political instability and forecasting.
- [ggthemr](https://github.com/cttobin/ggthemr) - Themes for ggplot2.
- [Miscellaneous-R-Code](https://github.com/m-clark/Miscellaneous-R-Code) - Code that might be useful to others for learning/demonstration purposes. ยฎ
- [quanteda](https://github.com/quanteda/quanteda) - An R package for the Quantitative Analysis of Textual Data
- [JAGSExamples](https://github.com/johnmyleswhite/JAGSExamples) - Examples of statistical models implemented using JAGS
- [R-tutorials](https://github.com/kenkellner/R-tutorials) - Short R and BUGS tutorials for beginners.
- [UBCadv-r](https://github.com/aammd/UBCadv-r) - Note sharing for a discussion group around the Advanced R Programming book (http://adv-r.had.co.nz/)
## Rich Text Format
- [striprtf](https://github.com/kota7/striprtf) - R Package for Extracting Text from RTF (Rich Text Format) File
## Roff
- [conceptnet5](https://github.com/commonsense/conceptnet5) - Code for building ConceptNet from raw data.
## Ruby
- [md2key](https://github.com/k0kubun/md2key) - Convert markdown to keynote
## Rust
- [xsv](https://github.com/BurntSushi/xsv) - A fast CSV command line toolkit written in Rust.
## Shell
- [kafka-learning](https://github.com/ziwon/kafka-learning) - Go from Zero to Hero in Kafka
- [apaxy](https://github.com/oupala/apaxy) - a simple, customisable theme for your apache directory listing
- [mac-dev-setup](https://github.com/nicolashery/mac-dev-setup) - A beginner's guide to setting up a development environment on macOS
## Stan
- [ssmodels-in-stan](https://github.com/jrnold/ssmodels-in-stan) - State space models (dynamic linear models, hidden Markov models) implemented in Stan.
## Stata
- [mostly-harmless-replication](https://github.com/vikjam/mostly-harmless-replication) - Replication of tables and figures from "Mostly Harmless Econometrics" in Stata, R, Python and Julia.
## Swift
- [Pock](https://github.com/pigigaldi/Pock) - Display macOS Dock in Touch Bar
## TeX
- [prob-stats](https://github.com/bob-carpenter/prob-stats) - Probability and Statistics: a simulation-based introduction. An open-access book.
- [rcpp4everyone_en](https://github.com/teuder/rcpp4everyone_en) - Rcpp for everyone
- [pfa](https://github.com/datamininggroup/pfa) - Portable Format for Analytics
- [R-for-Big-Data](https://github.com/Robinlovelace/R-for-Big-Data) - Teaching materials for handling large datasets in R
## TypeScript
- [terminus](https://github.com/Eugeny/terminus) - A terminal for a more modern age
- [md2googleslides](https://github.com/gsuitedevs/md2googleslides) - Generate Google Slides from markdown
- [vscode-r-lsp](https://github.com/REditorSupport/vscode-r-lsp) - R LSP Client for Visual Studio Code
- [reakit](https://github.com/reakit/reakit) - Toolkit for building accessible rich web apps with React
- [playground](https://github.com/tensorflow/playground) - Play with neural networks!
- [libRmath.js](https://github.com/R-js/libRmath.js) - Javascript Pure Implementation of Statistical R "core" numerical libRmath.so
- [Mstdn](https://github.com/rhysd/Mstdn) - Tiny web-based mastodon client for your desktop
## License
[](https://creativecommons.org/publicdomain/zero/1.0/)
To the extent possible under law, [robertmyles](https://github.com/robertmyles) has waived all copyright and related or neighboring rights to this work.