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Decision brief
Use scikit-learn for Python-based machine learning tasks that require robust algorithms, comprehensive documentation, and extensive community support.
Good fit when
- When you need a well-documented library with clear examples and strong community support.
- If your project relies on established machine learning models and requires minimal setup.
Avoid when
- Avoid if you require cutting-edge deep learning capabilities or model training that is more efficiently managed with GPU accelerators.
- Not ideal when dealing with very large datasets that benefit from out-of-core computation, as it lacks native support for such functionalities.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (1d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install scikit-learnHow it fits your stack(4)
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Integrates
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
scikit-learn is a Python module for machine learning that includes various algorithms and tools for data analysis and modeling.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Aug 3, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 3, 2026)
**scikit-learn** is a Python module for machine learning built on top ofSource link
Tags
README
.. -- mode: rst --
|GitHubActions| |Codecov| |CircleCI| |Nightly wheels| |Ruff| |PythonVersion| |PyPI| |DOI| |Benchmark|
.. |GitHubActions| image:: https://github.com/scikit-learn/scikit-learn/actions/workflows/unit-tests.yml/badge.svg? :target: https://github.com/scikit-learn/scikit-learn/actions/workflows/unit-tests.yml?query=branch%3Amain
.. |CircleCI| image:: https://circleci.com/gh/scikit-learn/scikit-learn/tree/main.svg?style=shield :target: https://circleci.com/gh/scikit-learn/scikit-learn
.. |Codecov| image:: https://codecov.io/gh/scikit-learn/scikit-learn/branch/main/graph/badge.svg?token=Pk8G9gg3y9 :target: https://codecov.io/gh/scikit-learn/scikit-learn
.. |Nightly wheels| image:: https://github.com/scikit-learn/scikit-learn/actions/workflows/wheels.yml/badge.svg?event=schedule :target: https://github.com/scikit-learn/scikit-learn/actions?query=workflow%3A%22Wheel+builder%22+event%3Aschedule
.. |Ruff| image:: https://img.shields.io/badge/code%20style-ruff-000000.svg? :target: https://github.com/astral-sh/ruff
.. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/scikit-learn.svg? :target: https://pypi.org/project/scikit-learn/
.. |PyPI| image:: https://img.shields.io/pypi/v/scikit-learn :target: https://pypi.org/project/scikit-learn
.. |DOI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.17880109.svg? :target: https://zenodo.org/badge/latestdoi/21369/scikit-learn/scikit-learn
.. |Benchmark| image:: https://img.shields.io/badge/Benchmarked%20by-asv-blue :target: https://scikit-learn.org/scikit-learn-benchmarks
.. |PythonMinVersion| replace:: 3.11 .. |NumPyMinVersion| replace:: 1.24.1 .. |SciPyMinVersion| replace:: 1.10.0 .. |JoblibMinVersion| replace:: 1.4.0 .. |NarwhalsMinVersion| replace:: 2.0.1 .. |ThreadpoolctlMinVersion| replace:: 3.5.0 .. |MatplotlibMinVersion| replace:: 3.6.1 .. |Scikit-ImageMinVersion| replace:: 0.22.0 .. |PandasMinVersion| replace:: 1.5.0 .. |SeabornMinVersion| replace:: 0.13.0 .. |PytestMinVersion| replace:: 7.1.2 .. |PlotlyMinVersion| replace:: 5.22.0
.. image:: https://raw.githubusercontent.com/scikit-learn/scikit-learn/main/doc/logos/scikit-learn-logo.png :target: https://scikit-learn.org/
scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.
The project was started in 2007 by David Cournapeau as a Google Summer
of Code project, and since then many volunteers have contributed. See
the About us <https://scikit-learn.org/dev/about.html#authors>__ page
for a list of core contributors.
It is currently maintained by a community of contributors, with volunteers but also support from several organisations <https://scikit-learn.org/dev/institutional_support.html>__.
Website: https://scikit-learn.org
Installation
Dependencies
scikit-learn requires:
- Python (>= |PythonMinVersion|)
- NumPy (>= |NumPyMinVersion|)
- SciPy (>= |SciPyMinVersion|)
- Narwhals (>= |NarwhalsMinVersion|)
- joblib (>= |JoblibMinVersion|)
- threadpoolctl (>= |ThreadpoolctlMinVersion|)
=======
Scikit-learn plotting capabilities (i.e., functions start with ``plot_`` and
classes end with ``Display``) require Matplotlib (>= |MatplotlibMinVersion|).
For running the examples Matplotlib >= |MatplotlibMinVersion| is required.
A few examples require scikit-image >= |Scikit-ImageMinVersion|, a few examples
require pandas >= |PandasMinVersion|, some examples require seaborn >=
|SeabornMinVersion| and Plotly >= |PlotlyMinVersion|.
User installation
If you already have a working installation of NumPy and SciPy,
the easiest way to install scikit-learn is using pip::
pip install -U scikit-learn
or conda::
conda install -c conda-forge scikit-learn
The documentation includes more detailed installation instructions <https://scikit-learn.org/stable/install.html>_.
Changelog
See the `changelog <https://scikit-learn.o
For agents
This page has a .md twin and JSON over the API.