About us#

History#

This project was started in 2007 as a Google Summer of Code project by David Cournapeau. Later that year, Matthieu Brucher started working on this project as part of his thesis.

In 2010 Fabian Pedregosa, Gael Varoquaux, Alexandre Gramfort and Vincent Michel of INRIA took leadership of the project and made the first public release, February the 1st 2010. Since then, several releases have appeared following an approximately 3-month cycle, and a thriving international community has been leading the development. As a result, INRIA holds the copyright over the work done by people who were employed by INRIA at the time of the contribution.

Governance#

The decision making process and governance structure of scikit-learn, like roles and responsibilities, is laid out in the governance document.

The people behind scikit-learn#

scikit-learn is a community project, developed by a large group of people, all across the world. A few core contributor teams, listed below, have central roles, however a more complete list of contributors can be found on GitHub.

Active Core Contributors#

Maintainers Team#

The following people are currently maintainers, in charge of consolidating scikit-learn’s development and maintenance:

Jérémie du Boisberranger

Loïc Estève

Thomas J. Fan

Alexandre Gramfort

Olivier Grisel

Tim Head

Adrin Jalali

Julien Jerphanion

Guillaume Lemaitre

Adam Li

Lucy Liu

Christian Lorentzen

Andreas Mueller

Joel Nothman

Omar Salman

Stefanie Senger

Gael Varoquaux

Yao Xiao

Meekail Zain

Note

Please do not email the authors directly to ask for assistance or report issues. Instead, please see What’s the best way to ask questions about scikit-learn in the FAQ.

Documentation Team#

The following people help with documenting the project:

Arturo Amor

Lucy Liu

Maren Westermann

Yao Xiao

Contributor Experience Team#

The following people are active contributors who also help with triaging issues, PRs, and general maintenance:

Virgil Chan

Juan Carlos Alfaro Jiménez

Maxwell Liu

Juan Martin Loyola

Dea María Léon

Sylvain Marié

Norbert Preining

Reshama Shaikh

Albert Thomas

Maren Westermann

Communication Team#

The following people help with communication around scikit-learn.

François Goupil

Emeritus Core Contributors#

Emeritus Maintainers Team#

The following people have been active contributors in the past, but are no longer active in the project:

Mathieu Blondel
Joris Van den Bossche
Matthieu Brucher
Lars Buitinck
David Cournapeau
Noel Dawe
Vincent Dubourg
Edouard Duchesnay
Alexander Fabisch
Virgile Fritsch
Satrajit Ghosh
Angel Soler Gollonet
Chris Gorgolewski
Jaques Grobler
Yaroslav Halchenko
Brian Holt
Nicolas Hug
Arnaud Joly
Thouis (Ray) Jones
Kyle Kastner
Manoj Kumar
Robert Layton
Wei Li
Paolo Losi
Gilles Louppe
Jan Hendrik Metzen
Vincent Michel
Jarrod Millman
Vlad Niculae
Alexandre Passos
Fabian Pedregosa
Peter Prettenhofer
Hanmin Qin
(Venkat) Raghav, Rajagopalan
Jacob Schreiber
杜世橋 Du Shiqiao
Bertrand Thirion
Tom Dupré la Tour
Jake Vanderplas
Nelle Varoquaux
David Warde-Farley
Ron Weiss
Roman Yurchak

Emeritus Communication Team#

The following people have been active in the communication team in the past, but no longer have communication responsibilities:

Lauren Burke-McCarthy
Reshama Shaikh

Emeritus Contributor Experience Team#

The following people have been active in the contributor experience team in the past:

Chiara Marmo

Citing scikit-learn#

If you use scikit-learn in a scientific publication, we would appreciate citations to the following paper:

Scikit-learn: Machine Learning in Python, Pedregosa et al., JMLR 12, pp. 2825-2830, 2011.

Bibtex entry:

@article{scikit-learn,
  title={Scikit-learn: Machine Learning in {P}ython},
  author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
          and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
          and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
          Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
  journal={Journal of Machine Learning Research},
  volume={12},
  pages={2825--2830},
  year={2011}
}

If you want to cite scikit-learn for its API or design, you may also want to consider the following paper:

API design for machine learning software: experiences from the scikit-learn project, Buitinck et al., 2013.

Bibtex entry:

@inproceedings{sklearn_api,
  author    = {Lars Buitinck and Gilles Louppe and Mathieu Blondel and
                Fabian Pedregosa and Andreas Mueller and Olivier Grisel and
                Vlad Niculae and Peter Prettenhofer and Alexandre Gramfort
                and Jaques Grobler and Robert Layton and Jake VanderPlas and
                Arnaud Joly and Brian Holt and Ga{\"{e}}l Varoquaux},
  title     = {{API} design for machine learning software: experiences from the scikit-learn
                project},
  booktitle = {ECML PKDD Workshop: Languages for Data Mining and Machine Learning},
  year      = {2013},
  pages = {108--122},
}

Branding & Logos#

The scikit-learn brand is subject to the following terms of use and guidelines.

High quality PNG and SVG logos are available in the doc/logos source directory. The color palette is available in the Branding Guide.

Institutional support#

scikit-learn is a community driven project, however institutional and private grants help to assure its sustainability.

More details about institutional support are available in the Institutional support section.

Coding Sprints#

The scikit-learn project has a long history of open source coding sprints with over 50 sprint events from 2010 to present day. There are scores of sponsors who contributed to costs which include venue, food, travel, developer time and more. See scikit-learn sprints for a full list of events.

scikit-learn Swag#

Official scikit-learn swag is available for purchase at the NumFOCUS online store. A portion of the proceeds from each sale goes to support the scikit-learn project.