Scikit-learn @ Inria Foundation

Fostering growth and sustainability of the reference machine-learning toolbox

with the help of our partners


Scikit-learn, a central tool in AI and data-science

Scikit-learn is a machine-learning library in Python. It is the engine that powers many applications of artifical intelligence and data science.

Scikit-learn is used on a regular basis by more than half a million of people in the world, with applications ranging from medical imaging to product recommendation.

More on scikit-learn


An open-source project

Scikit-learn is an open-source software, under a license that facilitates commercial usage. It is developed by a world-wide community, gathering many different expertise on statistics, algorithms and software production.

The quality of scikit-learn, its algorithms, its interfaces, its documentation, are universally acclaimed. Its development follows a strict process to ensure this quality.


The foundation’s missions

The goal of the foundation is to enable maintaining scikit-learn’s high standards addressing new challenges.

The foundation employs central contributors to the project, to support scikit-learn’s community and to develop new ambitious features. The priorities of the foundation are set jointly by the community and its sponsors.



Time to come out! scikit-learn 0.22

A new look and many new features for this 0.22 scikit-learn release. Just a bit earlier than Santa visiting, this past month some special Elves have worked really hard to keep the target of releasing scikit-learn twice a year. Come take a look at some of the many surprises this remarkable package contains. With big data come big responsibilities New features for plotting and interpretability Models fitted by…

Fujitsu joins the Consortium

Fujitsu Laboratories join the Consortium. Fujitsu will thereby contribute to the sustainability of the scikit-learn development community. More information is available via the press releases published by Inria and Fujitsu.


Technical Committee July 4, 2019   Priority list for the consortium at Inria, year 2019–2020   From the discussion during the technical committee, the scikit-learn consortium at Inria defined the following list of priorities for the coming year: Continue effort to help with project maintenance to keep the target to release twice a year. Development of the “inspect” module: Help finalize the pull requests for the newly introduced…