 Название: Natural Language Processing: A Textbook with Python Implementation, 2nd Edition
Автор: Raymond Lee
Издательство: Springer
Год: 2025
Страниц: 489
Язык: английский
Формат: pdf (true), epub
Размер: 73.0 MB
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.
This book is structured into two main parts: Part I—Concepts and Technology, and Part II—Natural Language Processing Workshops with Python Implementation in 14 Hours. In Part I, the first ten chapters lay a solid foundation in natural language processing (NLP) concepts, exploring key topics such as N-gram language models, part-of-speech tagging, syntax analysis, semantic representations, and latest advancements in transfer learning and transformer technology. Each chapter builds on the preceding one, leading to an understanding of major NLP applications and the evolution of large language models and generative AI, while also addressing ethical considerations in AI.
Part II consists of seven practical workshops that provide hands-on experience with Python implementations relevant to the concepts discussed in the first part. Starting with an introduction to the Natural Language Toolkit (NLTK), the workshops guide readers through various NLP tasks such as N-gram modeling, sentiment analysis, and use of transformers like BERT. Each workshop offers step-by-step instructions, empowering readers to apply their knowledge in real-world scenarios, including the creation and deployment of a chatbot system. This structured approach balances foundational theory with practical application, making it suitable for learners eager to advance their skills in NLP.
Readers of This Book:
This book serves as both an NLP textbook and a practical guide for NLP Python implementation, tailored for:
• Undergraduates and postgraduates across various disciplines, including AI, Computer Science, IT, Data Science, and related fields
• Lecturers and tutors teaching NLP or AI-related courses
• NLP and AI scientists, as well as developers, who wish to learn the fundamental concepts of NLP and apply them through Python-based workshops
• Readers interested in learning NLP concepts and practicing Python-based NLP techniques using tools such as NLTK, spaCy, TensorFlow, Keras, BERT, transformer technology, and latest developments in LLMs and GenAI
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Natural Language Processing: A Textbook with Python Implementation, 2nd Edition 
