This textbook provides a contemporary and comprehensive overview of Natural Language Processing (NLP), covering fundamental concepts, core algorithms, and key applications such as AI chatbots, Large Language Models and Generative AI. Additionally, it includes seven step-by-step NLP workshops, totaling 14 hours, that offer hands-on practice with essential Python tools, including NLTK, spaCy, TensorFlow, Keras, Transformers, and BERT.

The objective of this book is to provide readers with a fundamental grasp of NLP and its core technologies, and to enable them to build their own NLP applications (e.g. Chatbot systems) using Python-based NLP tools. It is both a textbook and NLP tool-book intended for the following readers: undergraduate students from various disciplines who want to learn NLP; lecturers and tutors who want to teach courses or tutorials for undergraduate/graduate students on NLP and related AI topics; and readers with various backgrounds who want to learn NLP, and more importantly, to build workable NLP applications after completing its 14 hours of Python-based workshops.

Table of Contents

Part I: Concepts and Technology

Chapter 1: Natural Language Processing

Chapter 2: N-Gram Language Model

Chapter 3: Part-of-Speech (POS) Tagging

Chapter 4: Syntax and Parsing

Chapter 5: Meaning Representation

Chapter 6: Semantic Analysis

Chapter 7: Pragmatic Analysis and Discourse

Chapter 8: Transfer Learning and Transformer Technology

Chapter 9: Major NLP Applications

Chapter 10: Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI)

Part II: Natural Language Processing Workshops with Python Implementation in 14 Hours

Chapter 11: Workshop#1: Basics of Natural Language Toolkit (Hour 1–2)

Chapter 12: Workshop#2: N-Grams Modeling with Natural Language Toolkit (Hour 3–4)

Chapter 13: Workshop#3: Part-of-Speech Tagging Using Natural Language Toolkit (Hour 5–6)

Chapter 14: Workshop#4 Semantic Analysis and Word Vectors Using spaCy (Hour 7–8)

Chapter 15: Workshop#5: Sentiment Analysis and Text Classification (Hour 9–10)

Chapter 16: Workshop#6 Transformers with spaCy and TensorFlow (Hour 11–12)

Chapter 17: Workshop#7 Building Chatbot with TensorFlow and Transformer Technology (Hour 13–14)

About the Author

Dr. Raymond Lee is the founder of the Quantum Finance Forecast System (QFFC) and currently serves as an Associate Professor at BNU-HKBU United International College (UIC). With over 25 years of experience in AI research and consultancy, Dr. Lee's expertise encompasses Chaotic Neural Networks, Natural Language Processing (NLP), Intelligent Fintech Systems, Quantum Finance, and Intelligent E-Commerce Systems. He has published more than 100 research papers and authored nine textbooks on topics such as AI, chaotic neural networks, AI-based fintech systems, intelligent agent technology, chaotic cryptosystems, ontological agents, neural oscillators, biometrics, and weather simulation and forecasting. In 2018, after completing the QFFC project, Dr. Lee joined UIC to further his research in AI-Fintech and to share his knowledge with students and the broader community. His three most recent textbooks: Quantum Finance: Intelligent Forecast and Trading Systems (2019), Artificial Intelligence in Daily Life (2020), and this NLP book have been adopted as core textbooks for various AI courses at UIC.