NeuPy is a Python library for Artificial Neural Networks.
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README.rst

NeuPy

NeuPy is a Python library for Artificial Neural Networks. You can run and test different Neural Network algorithms.

Travis

Installation

$ pip install neupy

Links

Dependence

  • Python 2.7, 3.3, 3.4
  • NumPy >= 1.9.0
  • SciPy >= 0.14.0
  • Matplotlib >= 1.4.0

Next steps

  • Bug fixing and version stabilization
  • Speeding up algorithms
  • Adding more algorithms

Library support

  • Radial Basis Functions Networks (RBFN)
  • Backpropagation and different optimization for it
  • Neural Network Ensembles
  • Associative and Autoasociative Memory
  • Competitive Networks
  • Step update algorithms for backpropagation
  • Weight control algorithms for backpropagation
  • Basic Linear Networks

Algorithms

  • Backpropagation
    • Classic Gradient Descent
    • Mini-batch Gradient Descent
    • Conjugate Gradient
      • Fletcher-Reeves
      • Polak-Ribiere
      • Hestenes-Stiefel
      • Conjugate Descent
      • Liu-Storey
      • Dai-Yuan
    • quasi-Newton
      • BFGS
      • DFP
      • PSB
      • SR1
    • Levenberg-Marquardt
    • Hessian diagonal
    • Momentum
    • RPROP
    • iRPROP+
    • QuickProp
  • Weight update rules
    • Weight Decay
    • Weight Elimination
  • Learning rate update rules
    • Adaptive Learning Rate
    • Error difference Update
    • Linear search by Golden Search or Brent
    • Wolfe line search
    • Search than converge
    • Simple Step Minimization
  • Ensembles
    • Mixture of Experts
    • Dynamically Averaged Network (DAN)
  • Radial Basis Functions Networks (RBFN)
    • Generalized Regression Neural Network (GRNN)
    • Probabilistic Neural Network (PNN)
    • Radial basis function K-means
  • Autoasociative Memory
    • Discrete BAM Network
    • CMAC Network
    • Discrete Hopfield Network
  • Competitive Networks
    • Adaptive Resonance Theory (ART1) Network
    • Self-Organizing Feature Map (SOFM or SOM)
  • Linear networks
    • Perceptron
    • LMS Network
    • Modified Relaxation Network
  • Associative
    • OJA
    • Kohonen
    • Instar
    • Hebb

Tests

$ pip install tox
$ tox