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a Haskell implementation of Deep Learning frameworks.

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vortex

Introduction

Vortex is designed to be a Haskell implementation of Deep Learning frameworks.However it still keep developing. We hope this tool support:

  • Common neural layer types, such as Sigmoid, Softmax, Relu, &etc.

  • Multiple optimazation algorithms. SGD and Aladelta is proposed.

  • Some real world deep learning models. For instance, CNN, RNN, LSTM are all necessery. Futher on We also hope the Neural Turning Machine(NTM) is not immature if possible.

  • Some interested DEMOS. Image Regresssion, Image Classification, Neural Art, language modeling, &etc.

TODO List (recent)

  • Common layers implementation: sigmoid, linear, softmax, relu, dropout.

  • Optimazation algorithms.

  • Image regression.

Install

TODO

Example

TODO

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a Haskell implementation of Deep Learning frameworks.

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