Foundations of Natural Language Processing

Foundations of Natural Language Processing offers a comprehensive introduction to the core principles, algorithms, and applications of NLP. Beginning with the basics of linguistics, the book explores phonology, morphology, syntax, and semantics, illustrating how these elements are represented and processed computationally.
It then progresses to cover essential computational methods, including text preprocessing, tokenization, stemming, and part-of-speech tagging, before introducing statistical and machine learning approaches such as n-gram models, hidden Markov models, and probabilistic parsing. The book further delves into advanced topics like word embeddings, neural networks, attention mechanisms, and transformers, which underpin state-of-the-art language models used in modern AI systems.
Applications of NLP—such as machine translation, sentiment analysis, information retrieval, and question answering—are discussed in detail, alongside evaluation metrics and ethical considerations in language technology. Each chapter integrates theoretical discussion with examples, exercises, and case studies to foster both comprehension and practical skill development.
Designed for students of computer science, linguistics, and AI, as well as researchers and developers, this book serves as both a foundational text and a practical reference. It empowers readers to understand, design, and implement NLP systems that bridge human language and computational intelligence.