Connect with scikit-learn developers through various channels for assistance, feedback, or contributions.

Mailing Lists

User Questions

Engage with the scikit-learn community and seek answers to your questions:

  • StackOverflow: Some scikit-learn developers support users using the [scikit-learn] tag.

  • General Machine Learning Queries: For broader machine learning discussions, visit Stack Exchange.

When posting questions:

  • Please use a descriptive question in the title field (e.g. no “Please help with scikit-learn!” as this is not a question)

  • Provide detailed context, expected results, and actual observations.

  • Include code and data snippets (preferably minimalistic scripts, up to ~20 lines).

  • Describe your data and preprocessing steps, including sample size, feature types (categorical or numerical), and the target for supervised learning tasks (classification type or regression).

Note: Avoid asking user questions on the bug tracker to keep the focus on development.

Bug Tracker

Encountered a bug? Report it on our issue tracker

Include in your report:

  • Steps or scripts to reproduce the bug.

  • Expected and observed outcomes.

  • Python or gdb tracebacks, if applicable.

  • The ideal bug report contains a short reproducible code snippet, this way anyone can try to reproduce the bug easily.

  • If your snippet is longer than around 50 lines, please link to a gist or a github repo.

Tip: Gists are Git repositories; you can push data files to them using Git.


Note: The scikit-learn Gitter room is no longer an active community. For live discussions and support, please refer to the other channels mentioned in this document.

Documentation Resources

This documentation is for 1.4.2. Find documentation for other versions here.

Older versions’ printable PDF documentation is available here. Building the PDF documentation is no longer supported in the website, but you can still generate it locally by following the building documentation instructions.