SIGs/ML

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(Interesting software waiting for being packaged)
(Machine Learning Packages)
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== Interesting software waiting for being packaged ==
 
== Interesting software waiting for being packaged ==
  
* [http://mahout.apache.org/ Apache Mahout]
 
* [https://pypi.python.org/pypi/astroML astroML]
 
 
* [https://pypi.python.org/pypi/bob bob - free signal-processing and machine learning toolbox]
 
* [https://pypi.python.org/pypi/bob bob - free signal-processing and machine learning toolbox]
 
* [https://pypi.python.org/pypi/copper copper - Fast, easy and intuitive machine learning prototyping]
 
* [https://pypi.python.org/pypi/copper copper - Fast, easy and intuitive machine learning prototyping]
Line 24: Line 22:
 
* [https://pypi.python.org/pypi/Monte Monte - machine learning in pure Python]
 
* [https://pypi.python.org/pypi/Monte Monte - machine learning in pure Python]
 
* [https://pypi.python.org/pypi/nolearn nolearn - Miscellaneous utilities for machine learning]
 
* [https://pypi.python.org/pypi/nolearn nolearn - Miscellaneous utilities for machine learning]
* [http://orange.biolab.si/ Orange]
 
* [http://www.clips.ua.ac.be/pages/pattern Pattern - Web mining module for Python]
 
 
* [https://pypi.python.org/pypi/pcSVM pcSVM]
 
* [https://pypi.python.org/pypi/pcSVM pcSVM]
 
* [https://pypi.python.org/pypi/Peach Peach - Python library for computational intelligence and machine learning]
 
* [https://pypi.python.org/pypi/Peach Peach - Python library for computational intelligence and machine learning]
Line 32: Line 28:
 
* [https://pypi.python.org/pypi/ramp Rapid Machine Learning Prototyping]
 
* [https://pypi.python.org/pypi/ramp Rapid Machine Learning Prototyping]
 
* [https://pypi.python.org/pypi/Reinforcement-Learning-Toolkit Reinforcement-Learning-Toolkit]
 
* [https://pypi.python.org/pypi/Reinforcement-Learning-Toolkit Reinforcement-Learning-Toolkit]
* [http://scikit-learn.org/ scikit-learn -Machine Learning in Python]
 
* [http://shogun-toolbox.org/ SHOGUN]
 
 
* [http://sourceforge.net/projects/weka/ Weka---Machine Learning Software in Java]
 
* [http://sourceforge.net/projects/weka/ Weka---Machine Learning Software in Java]
  
 
== Work in progress ==
 
== Work in progress ==
  
 
+
* [http://mahout.apache.org/ Apache Mahout]
 +
* [https://pypi.python.org/pypi/astroML astroML]
 +
* [http://orange.biolab.si/ Orange]
 +
* [http://www.clips.ua.ac.be/pages/pattern Pattern - Web mining module for Python]
 +
* [http://scikit-learn.org/ scikit-learn -Machine Learning in Python]
 +
* [http://shogun-toolbox.org/ SHOGUN]
  
 
== New packages ==
 
== New packages ==

Revision as of 12:44, 24 September 2013

Contents

Machine Learning SIG

The Machine Learning SIG, aims to make Fedora the best platform for all things related to Machine Learning.

Members

Björn Esser (besser82) <besser82@fedoraproject.org>

Machine Learning Packages

Interesting software waiting for being packaged

Work in progress

New packages

When submitting a new ml-related package for review, please add "Blocks: ML-SIG" to your review-request. After the review has been granted don't forget to remove it, when filing the SCM-request, please.

When you are filing your SCM-admin-request, you should make sure to request InitialCC for "ml-sig".

Example:

New Package SCM Request
=======================
Package Name: pkgname
Short Description: summary of package
Owners: foo bar
Branches: f18 f19 f20 el5 el6
InitialCC: ml-sig

Packages waiting for your review

You can find them on the ML-SIG review-tracker.

We would be glad, if you would take one or a few.  :)

Existing packages

You can find the existing ml-related packages on the PkgDB.

Categories

more to come soon.

What are we going to do?

more to come soon.

Participation

There is no formal process for participating; joining the mailing list, hanging out on IRC, or participating in meetings are all fantastic ways to get involved.

A little self-introduction on the mailing list would be nice, too. And, if you want to, add yourself to our members-section above.

Mailing list

IRC

We will likely hang out on irc.freenode.net at #fedora-ml. German members may want to come into #fedora-ml-de, too.

Haven't used IRC for communication before? More information on how to use IRC is available here.

Meetings

We shall have them, and see how it goes.

more to come soon.