This repository provides an educational implementation of adversarial autoencoders, a deep learning technique that combines autoencoders with adversarial training. It includes code for training autoencoders, exploring latent space, disentangling style and content, and performing semi-supervised classification using only 1000 labeled MNIST samples. The project comes with Medium blog posts explaining each concept.