About Awesome ML
Awesome ML turns the Awesome Machine Learning list into a directory you can browse two ways: by the programming language you work in, and by the job you need done. It covers 1,170 libraries across 32 languages.
The list has collected libraries for over a decade, and many of them have since stopped moving. Every entry here carries its GitHub stars and the date of its last commit, so the maintained projects stand out from the ones that were left behind.
How libraries are sorted
Languages come straight from the list's own sections. A library listed under several languages, such as XGBoost or MXNet, appears once, on every language page it belongs to.
Tasks start from the list's headings (computer vision, natural language processing, speech, data analysis). The GitHub topics and description of each project then add the tasks a heading can't express: a "general-purpose" toolkit that is really an NLP library, or a framework built for large language models.
What the activity marks mean
- Updated this year
- The repository's default branch received a commit in the last 12 months.
- Quiet for over a year
- The last commit is between one and three years old.
- No commits in 3+ years
- Often finished or abandoned. Still useful to read, risky to depend on.
- Archived
- The owner made the repository read-only on GitHub.
Libraries the list itself marks as deprecated carry a "Deprecated" tag. Entries hosted outside GitHub, such as CRAN packages or university pages, show no activity data.
Source and updates
The data comes from josephmisiti/awesome-machine-learning, maintained by its contributors and released under CC0 1.0. Awesome ML is an independent project and not affiliated with the list or its maintainers.
The site checks the list for changes every six hours and refreshes GitHub data at least once a day. The current data is from commit a613d9b, synced Oct 24, 2026. To add or correct a library, suggest it on the original list; changes show up here automatically.