nlp-tutorial

Why we included this project

lyeoni/nlp-tutorial gathers compact, well-commented PyTorch notebooks that walk through common NLP tasks on real datasets: classifying HuffPost news articles by category, gauging sentiment in IMDb reviews, matching Stack Exchange questions to answers, and neural machine translation. The examples are short enough to follow line by line, which suits someone who has read about NLP and wants to train a first model without drowning in framework boilerplate. They also show how CNNs, RNNs, and transformers get wired together in working code instead of staying theoretical. Note that the repo has not been updated since 2020, so treat it as a well-organized introduction rather than something to build on directly; the value is the clear progression of examples and the reproducible code.