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<rss version="2.0" xmlns:wfw="http://wellformedweb.org/CommentAPI/"><channel><title>mloss.org scikitlearn</title><link>http://mloss.org</link><description>Updates and additions to scikitlearn</description><language>en</language><lastBuildDate>Sat, 23 Feb 2013 18:00:14 -0000</lastBuildDate><item><title>scikitlearn 0.13.1</title><link>http://mloss.org/software/view/240/</link><description>&lt;html&gt;&lt;p&gt;scikit-learn is a Python module integrating classique machine learning algorithmes in the tightly-nit world of scientific Python packages
&lt;/p&gt;
&lt;p&gt;It aims to provide simple and efficient solutions to learning     problems that are accessible to everybody and reusable in various     contexts: machine-learning as a versatile tool for science and engineering.
&lt;/p&gt;&lt;/html&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">Bertrand Thirion, Edouard Duschenay, Vincent Michel, Gael Varoquaux, Olivier Grisel,  Jacob VanderPlas, alexandre granfort, fabian pedregosa, Andreas Mueller</dc:creator><pubDate>Sat, 23 Feb 2013 18:00:14 -0000</pubDate><comments>http://mloss.org/software/rss/comments/240</comments><guid>http://mloss.org/software/view/240/</guid><category>icml2010</category></item></channel></rss>