Is Haskell okay for prototyping machine learning models for research (discovery and exploration)

This page summarizes the projects mentioned and recommended in the original post on /r/haskell

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  • hasktorch

    Tensors and neural networks in Haskell

  • You might find the Deep Learning From The First Principles tutorials by Bogdan Penkovsky an interesting survey of native Haskell implementations of deep neural networks, and a bit more. It demonstrates some native charting capabilities, and Day 9 uses Hasktorch.

  • tensorflow

    Haskell bindings for TensorFlow

  • If you require JAX, you'll be out of luck using Haskell. But there is Hasktorch, http://hasktorch.org/, and Tensorflow bindings in Haskell, https://github.com/tensorflow/haskell. Both seem to be actively maintained.

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  • 10-days-of-grad

    Neural Networks and Deep Learning

  • You might find the Deep Learning From The First Principles tutorials by Bogdan Penkovsky an interesting survey of native Haskell implementations of deep neural networks, and a bit more. It demonstrates some native charting capabilities, and Day 9 uses Hasktorch.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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