Название: Natural Language Processing: A Textbook With Python Implementation Автор: Raymond S. T. Lee Издательство: Springer Год: 2024 Страниц: 454 Язык: английский Формат: pdf (true) Размер: 23,9 MB
This textbook presents an up-to-date and comprehensive overview of Natural Language Processing (NLP), from basic concepts to core algorithms and key applications. Further, it contains seven step-by-step NLP workshops (total length: 14 hours) offering hands-on practice with essential Python tools like NLTK, spaCy, TensorFlow Kera, Transformer 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.
Natural Language Processing (NLP) and its related applications become part of daily life with exponential growth of Artificial Intelligence (AI) in past decades. NLP applications including Information Retrieval (IR) systems, Text Summarization System, and Question-and-Answering (Chatbot) System became one of the prevalent topics in both industry and academia that had evolved routines and benefited immensely to a wide array of day-to-day services.
Readers of This Book This book is both an NLP textbook and NLP Python implementation book tailored for:
• Undergraduates and postgraduates of various disciplines including AI, Computer Science, IT, Data Science, etc. • Lecturers and tutors teaching NLP or related AI courses. • NLP, AI scientists and developers who would like to learn NLP basic concepts, practice and implement via Python workshops. • Readers who would like to learn NLP concepts, practice Python-based NLP workshops using various NLP implementation tools such as NLTK, spaCy, TensorFlow Keras, BERT, and Transformer technology.
How to Use This book? This book can be served as a textbook for undergraduates and postgraduate courses on Natural Language Processing, and a reference book for general readers who would like to learn key technologies and implement NLP applications with contemporary implementation tools such as NLTK, spaCy, TensorFlow, BERT, and Transformer technology.
Part I. Concepts and Technology 1. Natural Language Processing 2. N-Gram Language Model 3. Part-of-Speech (POS) Tagging 4. Syntax and Parsing 5. Meaning Representation 6. Semantic Analysis 7. Pragmatic Analysis and Discourse 8. Transfer Learning and Transformer Technology 9. Major NLP Applications Part II. Natural Language Processing Workshops with Python Implementation in 14 Hours 10. Workshop#1 Basics of Natural Language Toolkit (Hour 1–2) 11. Workshop#2 N-grams in NLTK and Tokenization in SpaCy (Hour 3–4) 12. Workshop#3 POS Tagging Using NLTK (Hour 5–6) 13. Workshop#4 Semantic Analysis and Word Vectors Using spaCy (Hour 7–8) 14. Workshop#5 Sentiment Analysis and Text Classification with LSTM Using spaCy (Hour 9–10) 15. Workshop#6 Transformers with spaCy and TensorFlow (Hour 11–12) 16. Workshop#7 Building Chatbot with TensorFlow and Transformer Technology (Hour 13–14)
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