Natural Language Processing
A Textbook with Python Implementation
(Sprache: Englisch)
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...
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Klappentext zu „Natural Language Processing “
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.Inhaltsverzeichnis zu „Natural Language Processing “
Part I - Concepts and Technology.- Chapter 1. Introduction to Natural Language Processing.- Chapter 2. N-gram Language Model.- Chapter 3. Part-of-Speech 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 Natural Language Processing Applications.- Part II -Natural Language Processing Workshops with Python Implementation in 14 Hours.- Chapter 10. Workshop#1 - Basics of Natural Language Toolkit (Hour 1-2).- Chapter 11. Workshop#2 - N-grams Modeling with Natural Language Toolkit (Hour 3-4).- Chapter 12. Workshop#3 - Part-of-Speech Tagging using Natural Language Toolkit (Hour 5-6).- Chapter 13. Workshop#4 - Semantic Analysis and Word Vectors using spaCy (Hour 7-8).- Chapter 14. Workshop#5 - Sentiment Analysis and Text Classification (Hour 9-10).- Chapter 15. Workshop#6 - Transformers with spaCy and TensorFlow (Hour11-12).- Chapter 16. Workshop#7 - Building Chatbot with TensorFlow and Transformer Technology (Hour 13-14).
Autoren-Porträt von Raymond S. T. Lee
Dr. Raymond Lee is the founder of Quantum Finance Forecast System and currently an Associate Professor at United International College (UIC) with 25+ years' experience in AI research and consultancy, Chaotic Neural Networks, NLP, Intelligent Fintech Systems, Quantum Finance, and Intelligent E-Commerce Systems. He has published over 100 publications and authored eight textbooks in the fields of AI, chaotic neural networks, AI-based fintech systems, intelligent agent technology, chaotic cryptosystems, ontological agents, neural oscillators, biometrics, and weather simulation and forecasting systems. Upon completion of the QFFC project, in 2018 he joined United International College (UIC), China to pursue further R&D work on AI-Fintech, and to share his expertise in AI-Fintech, chaotic neural networks and related intelligent systems with fellow students and the community. His two latest textbooks, Quantum Finance: Intelligent Forecast and Trading Systems (2019) and Artificial Intelligence in Daily Life (2020), have been the main textbooks for new AI courses at UIC since 2020Bibliographische Angaben
- Autor: Raymond S. T. Lee
- 2023, 1st ed. 2024, XXXII, 437 Seiten, Maße: 15,5 x 23,5 cm, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 9819919983
- ISBN-13: 9789819919987
Sprache:
Englisch
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