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= Machine Learning SIG =
= Machine Learning SIG =
The Machine Learning SIG, aims to make Fedora the best platform for all things related to [http://en.wikipedia.org/wiki/Machine_learning Machine Learning].
The Machine Learning SIG's goal is to make Fedora the best platform for all things related to [http://en.wikipedia.org/wiki/Machine_learning Machine Learning]. We aim to act a hub in the gap between the Astronomy, Bigdata, Fedora Medical and Science and Technology SIGs.
 
== Members ==
 
[[User:besser82|Björn Esser (besser82)]] <[mailto:besser82@fedoraproject.org besser82@fedoraproject.org]>
 
[[User:kushal124|Kushal Khandelwal (kushal124)]] <[mailto:kushalkhandelwal10@gmail.com kushalkhandelwal10@gmail.com]>
 
[[User:lupinix|Christian Dersch (lupinix)]] <[mailto:lupinix@fedoraproject.org lupinix@fedoraproject.org]>
 
[[User:dhanesh95|Dhanesh B. Sabane (dhanesh95)]] <[mailto:dhanesh95@fedoraproject.org dhanesh95@fedoraproject.org]>


= Machine Learning Packages =
= Machine Learning Packages =


== Work needed and interesting software ==
== Interesting software waiting for being packaged ==
 
* [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/ease ease - Machine learning based automated text classification library]
* [https://pypi.python.org/pypi/hyperspy hyperspy - Hyperspectral data analysis toolbox]
* [https://pypi.python.org/pypi/infer infer - machine learning toolkit for classification and assisted experimentation]
* [http://java-ml.sourceforge.net/ Java-ML]
* [https://pypi.python.org/pypi/milk milk - Machine Learning Toolkit]
* [https://pypi.python.org/pypi/MLizard MLizard - Machine Learning workflow automatization]
* [http://mlpy.sourceforge.net/ mlpy - Machine Learning Python]
* [https://pypi.python.org/pypi/mmlf Maja Machine Learning Framework]
* [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/pcSVM pcSVM]
* [https://pypi.python.org/pypi/Peach Peach - Python library for computational intelligence and machine learning]
* [http://pybrain.org/ PyBrain]
* [http://pyml.sourceforge.net/ PyML]
* [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/tradingmachine tradingmachine - backtester for financial algorithms]
* [http://sourceforge.net/projects/weka/ Weka - Machine Learning Software in Java]
* [https://pypi.python.org/pypi/zipline zipline - backtester for financial algorithms]
 
== Work in progress ==


more to come soon.
{|
! Package !! People involved !! Status !! Notes
|-
| [http://mahout.apache.org/ Apache Mahout] || [[User:Besser82 | besser82]]  || WIP ||
|-
| [https://pypi.python.org/pypi/astroML astroML] || [[User:lupinix|lupinix]] || DONE ||
|-
| [http://orange.biolab.si/ Orange] || [[User:Besser82 | besser82]] || WIP || depends on [[rhbug:1000829 | LINPACK]]
|-
| [http://www.clips.ua.ac.be/pages/pattern Pattern - Web mining module for Python] || [[User:kushal124|kushal124]] || WIP || depends on [[rhbug:1194576 | packaging]] and unbundling
|-
| [http://scikit-learn.org/ scikit-learn - Machine Learning in Python] ||  || review done, but needs unbundling  || depends on [[rhbug:999823 | unbundling]]
|-
| [http://shogun-toolbox.org/ SHOGUN] || [[User:Besser82 | besser82]] || DONE || [[User:Besser82/Changes/shogun | upcoming feature for F21]] Imported && Build
|}


== New packages ==
== New packages ==
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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.
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.
A little self-introduction on the mailing list would be nice, too. And, if you want to, add yourself to [[SIGs/ML#Members | our members-section above]].


== Mailing list ==
== Mailing list ==

Revision as of 14:33, 15 November 2016

Machine Learning SIG

The Machine Learning SIG's goal is to make Fedora the best platform for all things related to Machine Learning. We aim to act a hub in the gap between the Astronomy, Bigdata, Fedora Medical and Science and Technology SIGs.

Members

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

Kushal Khandelwal (kushal124) <kushalkhandelwal10@gmail.com>

Christian Dersch (lupinix) <lupinix@fedoraproject.org>

Dhanesh B. Sabane (dhanesh95) <dhanesh95@fedoraproject.org>

Machine Learning Packages

Interesting software waiting for being packaged

Work in progress

Package People involved Status Notes
Apache Mahout besser82 WIP
astroML lupinix DONE
Orange besser82 WIP depends on LINPACK
Pattern - Web mining module for Python kushal124 WIP depends on packaging and unbundling
scikit-learn - Machine Learning in Python review done, but needs unbundling depends on unbundling
SHOGUN besser82 DONE upcoming feature for F21 Imported && Build

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.