What is Auto-Encoders?

Autoencoders are a type of neural network used for unsupervised learning. They work by compressing the input data into a lower-dimensional latent space, and then reconstructing the original input from this compressed representation. This process forces the network to learn the most salient features of the data. Autoencoders are commonly used for dimensionality reduction, feature extraction, anomaly detection, and data denoising.