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annotate doc/v2_planning/existing_python_ml_libraries.txt @ 1036:89e76e6e074f

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XG added to optimization team
author Xavier Glorot <glorotxa@iro.umontreal.ca>
date Tue, 07 Sep 2010 12:08:37 -0400
parents 6da3747c4c1f
children 730c00950957
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Dumitru Erhan <dumitru.erhan@gmail.com>
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1 Committee members: GD, DWF, IG, DE
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2
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3 This committee will investigate the possibility of interfacing and/or
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4 borrowing from other Python machine learning libraries that exist out there.
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5 Some questions that we need to answer:
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6
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7 * How much should we try to interface with other libraries?
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8 * What parts can we and should we implement ourselves and what should we leave
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9 to the other libraries?
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11 Preliminary list of libraries to look at:
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12
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13 * Pybrain
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14 * MDP
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15 * Orange (http://www.ailab.si/orange/)
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16 * PyML (http://pyml.sourceforge.net/)
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17 * mlpy (https://mlpy.fbk.eu/)
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18 * APGL (http://packages.python.org/apgl/)
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19 * MontePython (http://montepython.sourceforge.net/)
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20 * Shogun python bindings
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21 * libsvm python bindings
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22 * scikits.learn
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23
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24 Also check out http://scipy.org/Topical_Software#head-fc5493250d285f5c634e51be7ba0f80d5f4d6443
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25 - scipy.org's ``topical software'' section on Artificial Intelligence and
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26 Machine Learning