Mercurial > pylearn
view doc/v2_planning/existing_python_ml_libraries.txt @ 1114:de153244c8e5
added example file for the formulas.
author | Frederic Bastien <nouiz@nouiz.org> |
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date | Tue, 14 Sep 2010 13:33:45 -0400 |
parents | 4eaf576c3e9a |
children | 0e12ea6ba661 |
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Committee members: GD, DWF, IG, DE This committee will investigate the possibility of interfacing and/or borrowing from other Python machine learning libraries that exist out there. Some questions that we need to answer: * How much should we try to interface with other libraries? * What parts can we and should we implement ourselves and what should we leave to the other libraries? Preliminary list of libraries to look at: * Pybrain Razvan * MDP Ian * Orange (http://www.ailab.si/orange/) Ian (but could trade) * PyML (http://pyml.sourceforge.net/) * mlpy (https://mlpy.fbk.eu/) Dumitru * APGL (http://packages.python.org/apgl/) Dumitru * MontePython (http://montepython.sourceforge.net/) Guillaume (but could trade) * Shogun python bindings * libsvm python bindings Ian (but could trade) * scikits.learn Guillaume (but could trade) Also check out http://scipy.org/Topical_Software#head-fc5493250d285f5c634e51be7ba0f80d5f4d6443 - scipy.org's ``topical software'' section on Artificial Intelligence and Machine Learning