Simple auto encoder

This document discusses simple autoencoders. It defines autoencoders and describes their basic architecture and training process. It outlines eight types of autoencoders and provides examples of their applications, such as denoising images, dimensionality reduction, and anomaly detection. While autoencoders are not as efficient as generative adversarial networks for image reconstruction, they are still useful for tasks like dimensionality reduction and anomaly detection.