Travis CircleCI Black PyPi Benchmark
About us page for a list of core contributors.It is currently maintained by a team of volunteers.
scikit-learn requires:
Scikit-learn 0.20 was the last version to support Python 2.7 and Python 3.4. scikit-learn 1.0 and later require Python 3.7 or newer. scikit-learn 1.1 and later require Python 3.8 or newer.
Scikit-learn plotting capabilities (i.e., functions start with plot_ and
classes end with "Display") require Matplotlib (>= 3.1.2).
For running the examples Matplotlib >= 3.1.2 is required.
A few examples require scikit-image >= 0.14.5, a few examples
require pandas >= 1.0.5, some examples require seaborn >=
0.9.0.
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 Changelog
We welcome new contributors of all experience levels. The scikit-learn community goals are to be helpful, welcoming, and effective. The Important links
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 our Testing
After installation, you can launch the test suite from outside the source
directory (you will need to have pytest >= 5.0.1 installed):
pytest sklearn
See the web page Submitting a Pull Request
Before opening a Pull Request, have a look at the full Contributing page to make sure your code complies with our guidelines: Project History
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 Help and Support
If you use scikit-learn in a scientific publication, we would appreciate citations:
