Natural Language Processing

A Textbook with Python Implementation

Specificaties
Paperback, blz. | Engels
Springer Nature Singapore | e druk, 2024
ISBN13: 9789819920013
Rubricering
Juridisch :
Springer Nature Singapore e druk, 2024 9789819920013
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

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.

Specificaties

ISBN13:9789819920013
Taal:Engels
Bindwijze:paperback
Uitgever:Springer Nature Singapore

Inhoudsopgave

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).

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