fei-nn: Train a neural network with MXNet in Haskell.

[ ai, bsd3, library, machine-learning, program ] [ Propose Tags ]

High level APIs to rain a neural network with MXNet in Haskell.

Versions [faq] 0.2.0
Dependencies aeson (>=1.2), attoparsec (>=0.13), attoparsec-binary (>=0.2), base (>=4.7 && <5.0), bytestring (>=0.10), containers (>=0.5), exceptions (>=0.8.3), fei-base, fei-nn, ghc-prim, graphviz, lens (>=4.12), mmorph (>=1.0.9), mtl (>=2.2.0), resourcet (>=1.1.8), template-haskell (>=2.12), text (>=1.2), time (<2.0), transformers-base (>=0.4.4), unordered-containers (>=0.2.8), vector (>=0.12) [details]
License BSD-3-Clause
Copyright Copyright: (c) 2018 Jiasen Wu
Author Jiasen Wu
Maintainer jiasenwu@hotmail.com
Category Machine Learning, AI
Home page http://github.com/pierric/fei-nn
Uploaded by JiasenWu at Tue Sep 17 16:06:36 UTC 2019
Distributions NixOS:0.2.0
Executables lenet
Downloads 75 total (14 in the last 30 days)
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Status Hackage Matrix CI
Docs not available [build log]
All reported builds failed as of 2019-09-17 [all 3 reports]

Modules

  • MXNet
    • MXNet.NN
      • MXNet.NN.Callback
      • DataIter
        • MXNet.NN.DataIter.Class
        • MXNet.NN.DataIter.Vec
      • MXNet.NN.EvalMetric
      • MXNet.NN.Initializer
      • MXNet.NN.Layer
      • MXNet.NN.LrScheduler
      • MXNet.NN.NDArray
      • MXNet.NN.Optimizer
      • MXNet.NN.Types
      • MXNet.NN.Utils
        • MXNet.NN.Utils.GraphViz

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