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{{admon/warning|The Machine Learning SIG is inactive and the information on this page is mostly out of date. The [[SIGs/AI-ML|AI/ML SIG]] has replaced this SIG and will be the better reference going forward.}} | |||
= 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 and also between all interesting projects related to machine learning in Fedora. | 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. | ||
Latest revision as of 16:03, 15 August 2023
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>
Christiano Anderson (canderson9) <canderson9@fedoraproject.org>
David Kirwan (dkirwan) <dkirwan@redhat.com>
Graham Williamson (willo) <willo@fedoraproject.org>
Tom Rix (trix) <trix@redhat.com>
Benson Muite (fed500) <fed500@fedoraproject.org>
Machine Learning Projects
Thoth
Thoth is a promising project which uses artificial intelligence to analyze and recommend software stack for artificial intelligence applications. It's based on an assumption that the proper combination of tools and libraries can have a significant impact on the performance of your project.
Thoth is now in the alpha state but it should be soon ready for beta testers.
Github organization: github.com/thoth-station
Optimized TensorFlow builds
The Artificial Intelligence Center of Excellence (AICoE) provides a simple Python package index with builds of Tensorflow optimized for Fedora/Centos/RHEL.
ML-Pack
ML-Pack is a lightweight C++ machine learning library that has Python and Julia bindings. It is available in Fedora repositories.
Shogun
Shogun is a machine learning toolbox with interfaces to a number of other languages including Python, Ruby and R.
Dlib
Dlib is an open source C++ machine learning library that can also be called from Python.
FANN
FANN(Fast Artificial Neural Network Library) is an open source C++ machine learning library with a wide variety of language bindings. It is available in Fedora repositories.
h2o
h2o is an open source Java machine learning library with Python and R bindings.
Machine Learning Packages
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
We have a new FAS group machine-learning-sig! Do you need any help maintaining your package? Let us know on the mailing list and give the group permissions for your package.
What are we going to do?
- We're gonna update this wiki page so it can serve as a hub of interesting projects, links to important content, RPM packages etc. Do you know about anything we should have here? Let us know!
- We'll help ML developers as much as we can. Do you need some help or some new RPM package in Fedora? Let us know!
- We'll try to make Fedora the best distribution for AI/ML developers and users. Do you know how? Let us know!
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.
Telegram
We also have a Telegram group since Flock 2019. You can find it at t.me/FedoraMLSIG
There is also a bridge between the Telegram group and the IRC channel so you can use only one platform to stay in touch.
Meetings
We shall have them, and see how it goes.
more to come soon.