Autoencoders

Autoencoders are a type of neural network used to learn efficient data representations in an unsupervised manner. They work by compressing the input data into a lower-dimensional "code" and then reconstructing the original input from this compressed representation. By forcing the network to learn a compressed version of the data, autoencoders can discover important features and reduce the dimensionality of the data, making it easier to process and analyze.

Visit the following resources to learn more:

• @article@What Is an Autoencoder? | IBM