Neural Networks / Machine Learning with Elixir/Erlang

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Hello peeps,

This is my first post on this forum and it’s partially caused by the amusement and appreciation for Data Analysis and Machine Learning tools that Python devs has, like Tensorflow for example.
I know that historical Python and Erlang was adopted in different fields.

My the question is - what options to learn and experiment an enthusiastic Elixir developer has?
I’m only aware of http://www.springer.com/gp/book/9781461444626 but it’s already 5 years old.

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Until someone puts in the work to provide an API to the underlying math heavy routines written in C and C++ , it’s unlikely that there will be much available for the BEAM languages. There has been a lot of work in python to make these libraries accessible.

There is a python “port” for the BEAM, http://erlport.org/ that will help somewhat, but the kind of floating point mutable data computations that ML requires really don’t map to the BEAM very well. They don’t map well to python’s compute model well either, but python has a very good interface for working with external libraries.

There are improvements coming in the BEAM ( dirty schedulers) that will help change this situation, but Elixir is starting well behind in this area.

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Saw these on the Elixir Slack, no idea how usable they are:

https://github.com/fredwu/stemmer

	stemmer - An English (Porter2) stemming implementation in Elixir.

https://github.com/fredwu/simple_bayes
simple_bayes - A Simple Bayes (a.k.a. Naive Bayes) implementation in Elixir.

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Also look at this thread:

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Recently watched https://www.youtube.com/watch?v=iMhBEVCgPdg and believe Garett summarized it pretty well

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