This repository provides a PyTorch implementation of the paper ‘Unsupervised Domain Adaptation by Backpropagation’, using adversarial training with a gradient reversal layer to learn domain-invariant features. The model learns to classify source domain data while simultaneously confusing a domain discriminator, enabling knowledge transfer to a target domain without labeled target samples. It implements the classic DANN architecture with a feature extractor, label classifier, and domain classifier.