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Scikit-learn: Machine Learning in Python
Fabian Pedregosa (INRIA Saclay - Ile de France), Gaël Varoquaux (INRIA Saclay - Ile de France), Alexandre Gramfort (INRIA Saclay - Ile de France), Vincent Michel (INRIA Saclay - Ile de France), Bertrand Thirion (INRIA Saclay - Ile de France), Olivier Grisel (LAMI), Mathieu Blondel (LAMI), Peter Prettenhofer (LAMI), Ron Weiss (LAMI), Vincent Dubourg (LAMI), Jake Vanderplas (LNAO), Alexandre Passos (LNAO), David Cournapeau (LNAO), Matthieu Brucher (LNAO), Matthieu Perrot (LNAO), Édouard Duchesnay (LNAO)
Abstract: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings. Source code, binaries, and documentation can be downloaded from http://scikit-learn.sourceforge.net.