AE
Autoencoders
An **autoencoder** is a type of artificial neural network used to learn efficient data codings in an unsupervised manner. The aim of an autoencoder is to learn a representation (encoding) for a set of data, typically for dimensionality reduction, by training the network to ignore signal “noise”. Along with the reduction side, a reconstructing side is learnt, where the autoencoder tries to generate from the reduced encoding a representation as close as possible to its original input, hence its name. 

Extracted from: [Wikipedia](https://en.wikipedia.org/wiki/Autoencoder)

Image source: [Wikipedia](https://en.wikipedia.org/wiki/Autoencoder#/media/File:Autoencoder_schema.png)