Generative-Models

Basic to advanced level of generative model with code.

Autoencoders..

-- autoencoders can be used for dimension reduction before the data is processed by other algorithms.

-- "If one trains an autoencoder in a compression context on pictures of dogs, it will not generalize well to an application requiring data compression on pictures of cars"

-- A typical autoencoder consists of multiple layers of progressively fewer neurons for encoding the original input called a bottleneck layer. One danger is that the resulting algorithms may be missing important dimensions for the problem if the bottleneck layer is too narrow.

Autoencoder Dimensionality Reduction

Autoencoder for Image Denoising