Table of Contents
0:00 Recap and unsupervised learning
2:19 Plan
3:09 Theory of autoencoders
7:29 Practice of autoencoders in PyTorch
11:19 Representation learning with autoencoders
15:55 Practicals
16:49 A simple autoencoder
20:10 Stacked autoencoders
22:16 Interpolation
22:29 Denoising autoencoder