TY  - BOOK
AU  - Lee,Raymond S.T.
ED  - SpringerLink (Online service)
TI  - Natural Language Processing: A Textbook with Python Implementation 
SN  - 9789819919994
AV  - QA76.9.N38 
U1  - 006.35 23
PY  - 2024///
CY  - Singapore
PB  - Springer Nature Singapore, Imprint: Springer
KW  - Natural language processing (Computer science)
KW  - Artificial intelligence
KW  - Computational intelligence
KW  - Machine learning
KW  - Python (Computer program language)
KW  - Data processing
KW  - Natural Language Processing (NLP)
KW  - Artificial Intelligence
KW  - Computational Intelligence
KW  - Machine Learning
KW  - Python
KW  - Data Science
N1  - 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)
N2  - 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
UR  - http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-99-1999-4
ER  -