- Common Neural Network modules (fully connected layers, non-linearities)
- Classification (SVM/Softmax) and Regression (L2) cost functions
- A MagicNet class for fully automatic neural network learning (automatic hyperparameter search and cross-validatations)
- Ability to specify and train Convolutional Networks that process images
- An experimental Reinforcement Learning module, based on Deep Q Learning.
Head over to Getting Started for a tutorial that lets you get up and running quickly, and discuss Documentation for all specifics.
The code is available on Github under MIT license and I warmly welcome pull requests for new features / layers / demos and miscellaneous improvements. The library is also available on npm for use in Nodejs, under name convnetjs.