Machine Learning Working Group

To develop the ecosystem on all aspects in the context of Machine Learning, from native compilation to high-level abstractions and auxiliary projects.

Long-term objectives

  • Integrate with state-of-the-art tools for native numerical compilation. The goal is to target different accelerators (CPU/GPU) and with different modes (AOT/JIT)

  • Provide high-level abstractions for different disciplines of machine learning, such as neural networks, supervised learning, clustering, etc

  • Develop auxiliary projects that are essential to numerical computing and machine learning efforts, such as interactive tools, plotting libraries, etc

Benefits to the community

  • Our goal is to enable the Erlang Ecosystem to be used for Machine Learning and other numerical computing tasks. We believe functional programming can be a good fit for numerical computing, especially as we move to higher-level abstractions.

  • The Machine Learning WG also plans to collaborate with other Working Groups on many efforts. For example, Build and Packaging can help us discuss how to ship precompiled libraries. The Machine Learning and Embedded WG can work together on to provide tooling that runs on the edge. The External Process Communication can assist us to integrate with native tools.

Why does this group require the Foundation

This working group can benefit from the foundation in several ways:

  • The foundation can provide us communication tools so the Machine Learning WG becomes the main hub for ML discussions in the ecosystem

  • The Foundation can facilitate collaboration with interested WGs and relevant efforts happening in the ecosystem

  • The Foundation can fund some of the tasks outlined in our long-term deliverables

Initial list of volunteers

  • José Valim (chair)
  • Sean Moriarity (chair)
  • Jason Goldberger
  • Jonatan Kłosko
  • Stas Versilov
  • Peer Stritzinger

Current Working Group Chairs

  • José Valim
  • Sean Moriarity
Peer Stritzinger
Peer Stritzinger
José Valim
José Valim
Sean Moriarity
Sean Moriarity
Stas Versilov
Stas Versilov
Jason Goldberger
Jason Goldberger
Jonatan Kłosko
Jonatan Kłosko
Jeff Smith
Jeff Smith
View our calendar

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Recent posts
Machine Learning WG updates - May 2021