What are all of the topics you should know in deep learning?
According to Wikipedia, Deep learning:
- 4 Deep learning architectures
- 4.1 Deep neural networks
- 4.2 Issues with deep neural networks
- 4.3 Deep belief networks
- 4.4 Convolutional neural networks
- 4.5 Convolutional Deep Belief Networks
- 4.6 Deep Boltzmann Machines
- 4.7 Stacked (Denoising) Auto-Encoders
- 4.8 Deep Stacking Networks
- 4.9 Tensor Deep Stacking Networks (T-DSN)
- 4.10 Spike-and-Slab RBMs (ssRBMs)
- 4.11 Compound Hierarchical-Deep Models
- 4.12 Deep Coding Networks
- 4.13 Deep Kernel Machines
- 4.14 Deep Q-Networks
See also my quick and dirty webpages: