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scikit-learn is a Python module for machine learning built on top ofSciPy and is distributed under the 3-Clause BSD license.

The project was started in 2007 by David Cournapeau as a Google Summerof Code project, and since then many volunteers have contributed. SeetheAbout us pagefor a list of core contributors.

It is currently maintained by a team of volunteers.

Website:https://scikit-learn.org

scikit-learn requires:

• Python (>= 3.10)
• NumPy (>= 1.22.0)
• SciPy (>= 1.8.0)
• joblib (>= 1.2.0)
• threadpoolctl (>= 3.1.0)

Scikit-learn plotting capabilities (i.e., functions start withplot_ andclasses end withDisplay) require Matplotlib (>= 3.5.0).For running the examples Matplotlib >= 3.5.0 is required.A few examples require scikit-image >= 0.19.0, a few examplesrequire pandas >= 1.4.0, some examples require seaborn >=0.9.0 and plotly >= 5.14.0.

If you already have a working installation of NumPy and SciPy,the easiest way to install scikit-learn is usingpip:

pip install -U scikit-learn

orconda:

conda install -c conda-forge scikit-learn

The documentation includes more detailedinstallation instructions.

See thechangelogfor a history of notable changes to scikit-learn.

We welcome new contributors of all experience levels. The scikit-learncommunity goals are to be helpful, welcoming, and effective. TheDevelopment Guidehas detailed information about contributing code, documentation, tests, andmore. We've included some basic information in this README.

• Official source code repo:https://github.com/scikit-learn/scikit-learn
• Download releases:https://pypi.org/project/scikit-learn/
• Issue tracker:https://github.com/scikit-learn/scikit-learn/issues

You can check the latest sources with the command:

git clone https://github.com/scikit-learn/scikit-learn.git

To learn more about making a contribution to scikit-learn, please see ourContributing guide.

After installation, you can launch the test suite from outside the sourcedirectory (you will need to havepytest >= 7.1.2 installed):

pytest sklearn

See the web pagehttps://scikit-learn.org/dev/developers/contributing.html#testing-and-improving-test-coveragefor more information.

Random number generation can be controlled during testing by settingtheSKLEARN_SEED environment variable.

Before opening a Pull Request, have a look at thefull Contributing page to make sure your code complieswith our guidelines:https://scikit-learn.org/stable/developers/index.html

The project was started in 2007 by David Cournapeau as a Google Summerof Code project, and since then many volunteers have contributed. SeetheAbout us pagefor a list of core contributors.

The project is currently maintained by a team of volunteers.

Note: scikit-learn was previously referred to as scikits.learn.

• HTML documentation (stable release):https://scikit-learn.org
• HTML documentation (development version):https://scikit-learn.org/dev/
• FAQ:https://scikit-learn.org/stable/faq.html

• Website:https://scikit-learn.org
• Blog:https://blog.scikit-learn.org
• Mailing list:https://mail.python.org/mailman/listinfo/scikit-learn

• GitHub Discussions:https://github.com/scikit-learn/scikit-learn/discussions
• Stack Overflow:https://stackoverflow.com/questions/tagged/scikit-learn
• Discord:https://discord.gg/h9qyrK8Jc8

• LinkedIn:https://www.linkedin.com/company/scikit-learn
• YouTube:https://www.youtube.com/channel/UCJosFjYm0ZYVUARxuOZqnnw/playlists
• Facebook:https://www.facebook.com/scikitlearnofficial/
• Instagram:https://www.instagram.com/scikitlearnofficial/
• TikTok:https://www.tiktok.com/@scikit.learn
• Bluesky:https://bsky.app/profile/scikit-learn.org
• Mastodon:https://mastodon.social/@sklearn@fosstodon.org

• Calendar:https://blog.scikit-learn.org/calendar/
• Logos & Branding:https://github.com/scikit-learn/scikit-learn/tree/main/doc/logos

If you use scikit-learn in a scientific publication, we would appreciate citations:https://scikit-learn.org/stable/about.html#citing-scikit-learn