Skip to main content

NeuPy is the Artificial Neural Network library implemented in Python.

Project description

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

Travis

Installation

$ pip install neupy

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

neupy-0.1.1.tar.gz (52.7 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page