This book mainly introduces the basic principles, methods, and applications of neural networks, deep learning, and natural language processing. The book is divided into 3 parts, each covering different topics: Part 1 (Chapters 1-3) introduces the fundamentals of neural networks and deep learning, including the origin and development of artificial neural networks, representation methods of neural networks, mathematical foundational theories, machine learning basics, and the concept of representation learning; Part 2 (Chapters 4 and 5) introduces natural language processing and transformer networks; Part 3 (Chapters 6-10) covers case studies in natural language processing, including methods and technologies for text classification tasks, entity recognition, text generation, text summarization, and review-based question-answering systems.