Denoising Autoencoders (DAE) -- How To Use Neural Networks to Clean Up Your Data

The most common type of Autoencoder is an Undercomplete Autocencoder which squeezes (encodes) data into fewer neurons (lower dimension) while removing "unimportant" information. It achieves that by training an encoder and decoder simultaneously, so the output neurons match inputs as closely as possible.