This article is continuation of my previous article which is complete guide to build CNN using pytorch and keras.

Taking input from standard datasets or custom datasets is already mentioned in complete guide to CNN using pytorch and keras. So we can start with necessary introduction to AutoEncoders and then implement one.

AutoEncoders

Auto Encoder is a neural network that learns encoding data with minimal loss of information.

There are many variants of above network. Some of them are:

Sparse AutoEncoder

This auto-encoder reduces overfitting by regularizing activation function hidden nodes.

Denoising AutoEncoder

This auto-encoder is trained by adding noise to input. This will remove noise from input at evaluation.

#keras #variational-autoencoder #pytorch