Glossary of Deep Learning: Autoencoder – Deeper Learning – Medium

An Autoencoder is neural network capable of unsupervised feature learning. Neural networks are typically used for supervised learning problems, trying to predict a target vector y from input vectors x. An Autoencoder network, however, tries to predict x from x, without the need for labels. Here the challenge is recreating the essence of the original input from compressed, noisy or corrupted data. The idea behind the Autoencoder is to build a network with a narrow hidden layer between Encoder and Decoder that serves as a compressed representation of the input data.