PyTorchNLPBook

Why we included this project

Delip Rao and Brian McMahan built this repository to hold the code and datasets behind their O'Reilly book Natural Language Processing with PyTorch, with one folder per chapter. It moves from PyTorch basics and perceptron-based sentiment classification through feed-forward and convolutional networks, word embeddings, sequence models, and on to attention and neural machine translation, and every step ships as runnable code rather than snippets to retype. That makes it useful for people who own the book and want the working versions, and equally for developers who skip the reading and just want to see how a packed sequence or an attention mechanism actually behaves in PyTorch. Teams bringing newcomers up to speed on deep learning for NLP can treat the chapter-by-chapter examples as a guided self-study track.