Article (Scientific journals)
Scikit-learn: Machine Learning in Python
Pedregosa, Fabian; Varoquaux, Gaël; Gramfort, Alexandre et al.
2012In arXiv e-prints, 1201
Peer reviewed
 

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Keywords :
Computer Science - Learning; Computer Science - Mathematical Software
Abstract :
[en] 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.org.
Disciplines :
Computer science
Author, co-author :
Pedregosa, Fabian
Varoquaux, Gaël
Gramfort, Alexandre
Michel, Vincent
Thirion, Bertrand
Grisel, Olivier
Blondel, Mathieu
Müller, Andreas
Nothman, Joel
Louppe, Gilles  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Big Data
Prettenhofer, Peter
Weiss, Ron
Dubourg, Vincent
Vanderplas, Jake
Passos, Alexandre
Cournapeau, David
Brucher, Matthieu
Perrot, Matthieu
Duchesnay, Édouard
More authors (9 more) Less
Language :
English
Title :
Scikit-learn: Machine Learning in Python
Publication date :
02 January 2012
Journal title :
arXiv e-prints
Volume :
1201
Peer reviewed :
Peer reviewed
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since 23 June 2018

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