What is this?
A curated, community-maintained list of machine learning frameworks, libraries, and software, organized by programming language.
A curated, community-maintained list of machine learning frameworks, libraries, and software, organized by programming language.Is this a tool I install, or just a reference list?It is just a markdown document of links — a reference list, not something you install or run. You click through to whichever framework or library catches your interest.
It is just a markdown document of links — a reference list, not something you install or run. You click through to whichever framework or library catches your interest.How is the list organized?Entries are grouped first by programming language (APL, C, C++, Java, JavaScript, Python, R, Rust, Scala, Swift, and dozens more), then subdivided into categories such as Computer Vision, NLP, General-Purpose Machine Learning, and Data Visualization within each language.
Entries are grouped first by programming language (APL, C, C++, Java, JavaScript, Python, R, Rust, Scala, Swift, and dozens more), then subdivided into categories such as Computer Vision, NLP, General-Purpose Machine Learning, and Data Visualization within each language.Are the entries kept up to date and vetted?Yes — a listed repo is marked deprecated if its owner says it's unmaintained or it hasn't had a commit in 2-3 years. New PRs now require emailing the maintainer for manual human verification, since LLM-generated PRs became too numerous to review normally.
Yes — a listed repo is marked deprecated if its owner says it's unmaintained or it hasn't had a commit in 2-3 years. New PRs now require emailing the maintainer for manual human verification, since LLM-generated PRs became too numerous to review normally.Does it cover just Python, or other languages too?It spans nearly every language used in ML — Python, R, Java, C/C++, JavaScript, Julia, Rust, Go, Scala, Swift, Kotlin, Ruby, Haskell, and more — so it's useful regardless of your stack.
It spans nearly every language used in ML — Python, R, Java, C/C++, JavaScript, Julia, Rust, Go, Scala, Swift, Kotlin, Ruby, Haskell, and more — so it's useful regardless of your stack.Does this list include things besides software, like books or courses?Yes — the README links out to separate curated lists of free machine learning books, professional ML events, free online ML courses, and data science blogs and newsletters.
Yes — the README links out to separate curated lists of free machine learning books, professional ML events, free online ML courses, and data science blogs and newsletters.Can I see how popular this project is over time?The README embeds a 'Star History' chart that tracks the repo's GitHub star growth over time.
The README embeds a 'Star History' chart that tracks the repo's GitHub star growth over time.Does every language section cover deep learning specifically?Most languages have a dedicated 'Deep Learning' or 'General-Purpose Machine Learning' subsection listing frameworks like Caffe, CNTK, MXNet, DyNet, and LightGBM.
Most languages have a dedicated 'Deep Learning' or 'General-Purpose Machine Learning' subsection listing frameworks like Caffe, CNTK, MXNet, DyNet, and LightGBM.What are similar projects?Machine-Learning-Tutorials, Awesome-pytorch-list, 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code, awesome-tensorflow, deep-learning-drizzle, ds-cheatsheets, go, DeepLearning
Machine-Learning-Tutorials, Awesome-pytorch-list, 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code, awesome-tensorflow, deep-learning-drizzle, ds-cheatsheets, go, DeepLearningWhich topics is it in?r, natural-language-processing, speech-recognition, reinforcement-learning, data-visualization, nlp, data-science, awesome, computer-vision, cpp, java, awesome-list
r, natural-language-processing, speech-recognition, reinforcement-learning, data-visualization, nlp, data-science, awesome, computer-vision, cpp, java, awesome-list