Name: HaskellNN Version: 0.1.1 License: GPL License-file: LICENSE Author: Kiet Lam Maintainer: Kiet Lam Synopsis: High Performance Neural Network in Haskell Description: High Performance Neural Network in Haskell . Provides fast training algorithms using hmatrix's bindings to GSL and custom bindings to the liblbfgs C-library . Supported training algorithms: Gradient Descent, Conjugate Gradient, BFGS, LBFGS . - Users should focus on "AI.Model" for most usages (classification / regression) . - Other modules are provided for user expansion if needed . Go to for examples and tests for usage Category: AI Build-type: Simple Cabal-version: >= 1.6 Library Build-depends: base >= 4 && < 5, hmatrix >= 0.13.0.0, random Extensions: ForeignFunctionInterface hs-source-dirs: src Exposed-modules: AI.Calculation, AI.Calculation.Activation, AI.Calculation.Cost, AI.Calculation.Gradients, AI.Calculation.NetworkOutput, AI.Signatures, AI.Model, AI.Model.Classification, AI.Model.General, AI.Model.GenericModel, AI.Training, AI.Network Other-modules: AI.Training.Internal, AI.Training.Internal.LBFGSAux ghc-prof-options: -prof -auto-all Include-Dirs: cbits C-sources: src/AI/Training/Internal/lbfgs_aux.c, cbits/lbfgs.c cbits/lbfgs.h Includes: lbfgs.h source-repository head type: git location: https://github.com/ktklam9/HaskellNN