nlp

Why we included this project

Written in Chinese and kept as an evolving open-source book rather than a fixed library, this repository walks through the mechanics of classic machine-learning NLP: bag-of-words and TF-IDF features, Word2Vec and Doc2Vec embeddings, MLP and fastText classifiers, LDA topic modeling, and TextRank keyword extraction. Each chapter stands alone as a tutorial with code you can run yourself, which helps a developer see how the algorithms actually behave before wiring them into a production pipeline. The author's security background shows throughout: the book applies NLP to spam filtering and content moderation, areas where rule-based systems keep falling short. If you read Chinese and learn best from hands-on examples rather than theory, this is a practical place to start.