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Natural language processinga textbook with Python implementation /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Natural language processingby Raymond Lee.
Reminder of title:	a textbook with Python implementation /
Author:	Lee, Raymond S. T.
Published:	Singapore :Springer Nature Singapore :2025.
Description:	xxvi, 477 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Natural language processing (Computer science)
Online resource:	https://doi.org/10.1007/978-981-96-3208-4
ISBN:	9789819632084$q(electronic bk.)

Natural language processinga textbook with Python implementation /
Lee, Raymond S. T.

Natural language processinga textbook with Python implementation /[electronic resource] :by Raymond Lee. - 2nd ed. 2025. - Singapore :Springer Nature Singapore :2025. - xxvi, 477 p. :ill., digital ;24 cm.

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).

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.

ISBN: 9789819632084$q(electronic bk.)

Standard No.: 10.1007/978-981-96-3208-4doiSubjects--Topical Terms:

200539
Natural language processing (Computer science)

LC Class. No.: QA76.9.N38 / L44 2025

Dewey Class. No.: 006.35

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505 0 $a 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).
520 $a 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.
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