Autoencoders are a type of artificial neural network used for unsupervised learning of efficient codings. They work by encoding the input into a latent space representation and then decoding it back to the original input. This process helps in dimensionality reduction and feature learning, making them highly useful in various applications including image processing and anomaly detection.
