Deep learning libraries in python

Theano

Theano is a generic mathematical expression evaluation library. The main advantage is, it compiles to either CPU or GPU. By default it uses cpu. 

Download from http://deeplearning.net/software/theano/

Tutorial http://deeplearning.net/software/theano/tutorial/index.html#tutorial

Pylearn2

Pylearn2 is based on theano. So you can get advantage of running on GPU.

Download from https://github.com/lisa-lab/pylearn2

Models

• Logistic Regression 
• K-means 
• Multilayer Perceptron (MLP)
• Restricted Boltzmann Machines (RBM)
• Deep Boltzmann Machines (DBM)
• Ising 
• Auto Encoder: Autoencoders, denoising autoencoders, and stacked DAEs.
• Maxout Networks (Maxout)

It is not limited to above models and any one can add new model. Above models are pre implemented.

Hebel

It is also GPU accelerated deep learning library. Its based on PyCuda.

Models

• Logistic Regression
• Neural network regression
• Muti-Task neural net

Download from https://github.com/hannes-brt/hebel

Deepnet

GPU accelerated. Based on cudamat. 

Models

• Feed-forward Neural Nets
• Restricted Boltzmann Machines
• Deep Belief Nets
• Autoencoders
• Deep Boltzmann Machines
• Convolutional Neural Nets

Download from https://github.com/nitishsrivastava/deepnet

Others

Python tutorial on Restricted Bolzmann Machines - https://github.com/echen/restricted-boltzmann-machines

Modular Restricted Bolzmann machine implementation. Its based on theano. https://github.com/benanne/morb

Matrix Library for cuda - https://github.com/deeplearningais/CUV