This repository aims at helping people start practically with deep learning with very detailed examples. The implementation of very popular architectures are presented in notebooks with useful comments and links. Some less classical and more novel architectures but yet powerful are also presented.
Most examples are presented in both TensorFlow (python) and Torch (Lua).
Below, some good material to get started with deep learning:
- CS231n: Convolutional Neural Networks for Visual Recognition. A series of great and in-depth video lectures by Andrej Karpathy from the Computer Science department of Stanford University,
- Deep Learning, Ian Goodfellow, Yoshua Bengio, and Aaron Courville (2016). An extensive book worth reading,
- Deep learning lectures by Nando de Freitas from the Computer Science department of Oxford University.