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-*- mode: rst -*-\n\n|Azure| |Codecov| |CircleCI| |Nightly wheels| |Ruff| |PythonVersion| |PyPI| |DOI| |Benchmark|\n\n.. |Azure| image:: https://dev.azure.com/scikit-learn/scikit-learn/_apis/build/status/scikit-learn.scikit-learn?branchName=main\n   :target: https://dev.azure.com/scikit-learn/scikit-learn/_build/latest?definitionId=1\u0026branchName=main\n\n.. |CircleCI| image:: https://circleci.com/gh/scikit-learn/scikit-learn/tree/main.svg?style=shield\n   :target: https://circleci.com/gh/scikit-learn/scikit-learn\n\n.. |Codecov| image:: https://codecov.io/gh/scikit-learn/scikit-learn/branch/main/graph/badge.svg?token=Pk8G9gg3y9\n   :target: https://codecov.io/gh/scikit-learn/scikit-learn\n\n.. |Nightly wheels| image:: https://github.com/scikit-learn/scikit-learn/actions/workflows/wheels.yml/badge.svg?event=schedule\n   :target: https://github.com/scikit-learn/scikit-learn/actions?query=workflow%3A%22Wheel+builder%22+event%3Aschedule\n\n.. |Ruff| image:: https://img.shields.io/badge/code%20style-ruff-000000.svg\n   :target: https://github.com/astral-sh/ruff\n\n.. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/scikit-learn.svg\n   :target: https://pypi.org/project/scikit-learn/\n\n.. |PyPI| image:: https://img.shields.io/pypi/v/scikit-learn\n   :target: https://pypi.org/project/scikit-learn\n\n.. |DOI| image:: https://zenodo.org/badge/21369/scikit-learn/scikit-learn.svg\n   :target: https://zenodo.org/badge/latestdoi/21369/scikit-learn/scikit-learn\n\n.. |Benchmark| image:: https://img.shields.io/badge/Benchmarked%20by-asv-blue\n   :target: https://scikit-learn.org/scikit-learn-benchmarks\n\n.. |PythonMinVersion| replace:: 3.11\n.. |NumPyMinVersion| replace:: 1.24.1\n.. |SciPyMinVersion| replace:: 1.10.0\n.. |JoblibMinVersion| replace:: 1.3.0\n.. |ThreadpoolctlMinVersion| replace:: 3.2.0\n.. |MatplotlibMinVersion| replace:: 3.6.1\n.. |Scikit-ImageMinVersion| replace:: 0.22.0\n.. |PandasMinVersion| replace:: 1.5.0\n.. |SeabornMinVersion| replace:: 0.13.0\n.. |PytestMinVersion| replace:: 7.1.2\n.. |PlotlyMinVersion| replace:: 5.18.0\n\n.. image:: https://raw.githubusercontent.com/scikit-learn/scikit-learn/main/doc/logos/scikit-learn-logo.png\n  :target: https://scikit-learn.org/\n\n**scikit-learn** is a Python module for machine learning built on top of\nSciPy and is distributed under the 3-Clause BSD license.\n\nThe project was started in 2007 by David Cournapeau as a Google Summer\nof Code project, and since then many volunteers have contributed. See\nthe `About us \u003chttps://scikit-learn.org/dev/about.html#authors\u003e`__ page\nfor a list of core contributors.\n\nIt is currently maintained by a team of volunteers.\n\nWebsite: https://scikit-learn.org\n\nInstallation\n------------\n\nDependencies\n~~~~~~~~~~~~\n\nscikit-learn requires:\n\n- Python (\u003e= |PythonMinVersion|)\n- NumPy (\u003e= |NumPyMinVersion|)\n- SciPy (\u003e= |SciPyMinVersion|)\n- joblib (\u003e= |JoblibMinVersion|)\n- threadpoolctl (\u003e= |ThreadpoolctlMinVersion|)\n\n=======\n\nScikit-learn plotting capabilities (i.e., functions start with ``plot_`` and\nclasses end with ``Display``) require Matplotlib (\u003e= |MatplotlibMinVersion|).\nFor running the examples Matplotlib \u003e= |MatplotlibMinVersion| is required.\nA few examples require scikit-image \u003e= |Scikit-ImageMinVersion|, a few examples\nrequire pandas \u003e= |PandasMinVersion|, some examples require seaborn \u003e=\n|SeabornMinVersion| and Plotly \u003e= |PlotlyMinVersion|.\n\nUser installation\n~~~~~~~~~~~~~~~~~\n\nIf you already have a working installation of NumPy and SciPy,\nthe easiest way to install scikit-learn is using ``pip``::\n\n    pip install -U scikit-learn\n\nor ``conda``::\n\n    conda install -c conda-forge scikit-learn\n\nThe documentation includes more detailed `installation instructions \u003chttps://scikit-learn.org/stable/install.html\u003e`_.\n\n\nChangelog\n---------\n\nSee the `changelog \u003chttps://scikit-learn.org/dev/whats_new.html\u003e`__\nfor a history of notable changes to scikit-learn.\n\nDevelopment\n-----------\n\nWe welcome new contributors of all experience levels. The scikit-learn\ncommunity goals are to be helpful, welcoming, and effective. The\n`Development Guide \u003chttps://scikit-learn.org/stable/developers/index.html\u003e`_\nhas detailed information about contributing code, documentation, tests, and\nmore. We've included some basic information in this README.\n\nImportant links\n~~~~~~~~~~~~~~~\n\n- Official source code repo: https://github.com/scikit-learn/scikit-learn\n- Download releases: https://pypi.org/project/scikit-learn/\n- Issue tracker: https://github.com/scikit-learn/scikit-learn/issues\n\nSource code\n~~~~~~~~~~~\n\nYou can check the latest sources with the command::\n\n    git clone https://github.com/scikit-learn/scikit-learn.git\n\nContributing\n~~~~~~~~~~~~\n\nTo learn more about making a contribution to scikit-learn, please see our\n`Contributing guide\n\u003chttps://scikit-learn.org/dev/developers/contributing.html\u003e`_.\n\nTesting\n~~~~~~~\n\nAfter installation, you can launch the test suite from outside the source\ndirectory (you will need to have ``pytest`` \u003e= |PytestMinVersion| installed)::\n\n    pytest sklearn\n\nSee the web page https://scikit-learn.org/dev/developers/contributing.html#testing-and-improving-test-coverage\nfor more information.\n\n    Random number generation can be controlled during testing by setting\n    the ``SKLEARN_SEED`` environment variable.\n\nSubmitting a Pull Request\n~~~~~~~~~~~~~~~~~~~~~~~~~\n\nBefore opening a Pull Request, have a look at the\nfull Contributing page to make sure your code complies\nwith our guidelines: https://scikit-learn.org/stable/developers/index.html\n\nProject History\n---------------\n\nThe project was started in 2007 by David Cournapeau as a Google Summer\nof Code project, and since then many volunteers have contributed. See\nthe `About us \u003chttps://scikit-learn.org/dev/about.html#authors\u003e`__ page\nfor a list of core contributors.\n\nThe project is currently maintained by a team of volunteers.\n\n**Note**: `scikit-learn` was previously referred to as `scikits.learn`.\n\nHelp and Support\n----------------\n\nDocumentation\n~~~~~~~~~~~~~\n\n- HTML documentation (stable release): https://scikit-learn.org\n- HTML documentation (development version): https://scikit-learn.org/dev/\n- FAQ: https://scikit-learn.org/stable/faq.html\n\nCommunication\n~~~~~~~~~~~~~\n\nMain Channels\n^^^^^^^^^^^^^\n\n- **Website**: https://scikit-learn.org\n- **Blog**: https://blog.scikit-learn.org\n- **Mailing list**: https://mail.python.org/mailman/listinfo/scikit-learn\n\nDeveloper \u0026 Support\n^^^^^^^^^^^^^^^^^^^^^^\n\n- **GitHub Discussions**: https://github.com/scikit-learn/scikit-learn/discussions\n- **Stack Overflow**: https://stackoverflow.com/questions/tagged/scikit-learn\n- **Discord**: https://discord.gg/h9qyrK8Jc8\n\nSocial Media Platforms\n^^^^^^^^^^^^^^^^^^^^^^\n\n- **LinkedIn**: https://www.linkedin.com/company/scikit-learn\n- **YouTube**: https://www.youtube.com/channel/UCJosFjYm0ZYVUARxuOZqnnw/playlists\n- **Facebook**: https://www.facebook.com/scikitlearnofficial/\n- **Instagram**: https://www.instagram.com/scikitlearnofficial/\n- **TikTok**: https://www.tiktok.com/@scikit.learn\n- **Bluesky**: https://bsky.app/profile/scikit-learn.org\n- **Mastodon**: https://mastodon.social/@sklearn@fosstodon.org\n\nResources\n^^^^^^^^^\n\n- **Calendar**: https://blog.scikit-learn.org/calendar/\n- **Logos \u0026 Branding**: https://github.com/scikit-learn/scikit-learn/tree/main/doc/logos\n\nCitation\n~~~~~~~~\n\nIf you use scikit-learn in a scientific publication, we would appreciate citations: https://scikit-learn.org/stable/about.html#citing-scikit-learn\n","funding_links":["https://numfocus.org/donate-to-scikit-learn"],"categories":["Python","Machine_Learning","Multipurpose","Uncategorized","Data Science","Repos","Machine Learning","Basic Components","机器学习框架","Training","Statistics / Machine Learning building blocks","Frameworks-for-Training","Table of Contents","Libraries \u0026 Toolkits","Frameworks for Training","Machine Learning Framework","Software","Projects with Great Documentation","Awesome Tools","Curated List","Computation and Communication Optimisation","statistics","AI Projects: Step by Steps","Libraries, Softwares","📚 فهرست","Frameworks and libraries","Programming languages","🤖 Machine Learning \u0026 AI","General tools","Library"],"sub_categories":["Uncategorized","Cryptocurrencies","Fundamental libraries","Frameworks for Training","Popular-LLM","Algorithm libraries","General Purpose Framework","Some projects with more that 10 000 lines of Cython code","Languages","Machine Learning Tools","Misc","Frameworks","Library","کتابخانه هاي تحليل داده",":snake: Python","Python","Tools","3. 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