/deeppy

Deep learning in Python

Primary LanguagePythonMIT LicenseMIT

Deep learning in Python

DeepPy tries to combine state-of-the-art deep learning models with a Pythonic interface in an extensible framework.

Features

  • Pythonic programming interface based on NumPy's ndarray.
  • Runs on CPU or Nvidia GPUs when available (thanks to CUDArray).
  • Feedforward networks
    • Dropout layers.
    • Convnets layers: Convolution, pooling, local response normalization.
  • Siamese Networks
  • Training module
    • Stochastic gradient descent.
    • Interchangeable learning rules: Momentum, RMSProp.
    • Regularization: L2 weight decay.
  • Dataset module
    • MNIST, CIFAR10

Installation

First, install CUDArray. Then install DeepPy with the standard

python setup.py install

TODO

  • Dropout normalization of weights.
  • Documentation!
  • Support for regression problems in feed forward neural network.
  • Other network types (autoencoders, stochastic neural networks, etc.).
  • Interactive training method with visualization.

Influences

Thanks to the following projects for showing the way.