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= Machine Learning SIG = | = Machine Learning SIG = | ||
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. | 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 and also between all interesting projects related to machine learning in Fedora. | ||
== Members == | == Members == | ||
Revision as of 11:21, 25 June 2019
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 and also between all interesting projects related to machine learning in Fedora.
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>
Lumír Balhar (lbalhar) <lbalhar@redhat.com>
Machine Learning Packages
Interesting software waiting for being packaged
- bob - free signal-processing and machine learning toolbox
- copper - Fast, easy and intuitive machine learning prototyping
- ease - Machine learning based automated text classification library
- hyperspy - Hyperspectral data analysis toolbox
- infer - machine learning toolkit for classification and assisted experimentation
- Java-ML
- milk - Machine Learning Toolkit
- MLizard - Machine Learning workflow automatization
- mlpy - Machine Learning Python
- Maja Machine Learning Framework
- Monte - machine learning in pure Python
- nolearn - Miscellaneous utilities for machine learning
- pcSVM
- Peach - Python library for computational intelligence and machine learning
- PyBrain
- PyML
- Rapid Machine Learning Prototyping
- Reinforcement-Learning-Toolkit
- tradingmachine - backtester for financial algorithms
- Weka - Machine Learning Software in Java
- zipline - backtester for financial algorithms
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.