What do you know about Autoencoders?

Autoencoder is an unsupervised artificial neural network that learns how to efficiently compress and encode data then learns how to reconstruct the data back from the reduced encoded representation to a representation that is as close to the original input as possible.

Autoencoder, by design, reduces data dimensions by learning how to ignore the noise in the data.

Here is an example of the input/output image from the MNIST dataset to an autoencoder.