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Natural Language Processing : A Textbook with Python Implementation / by Raymond S. T. Lee.
Springer Nature - Springer Computer Science eBooks 2024 English International Available online
View online- Format:
- Book
- Author/Creator:
- Lee, Raymond S. T.
- Series:
- Computer Science Series
- Language:
- English
- Subjects (All):
- Natural language processing (Computer science).
- Artificial intelligence.
- Computational intelligence.
- Machine learning.
- Python (Computer program language).
- Artificial intelligence--Data processing.
- Natural Language Processing (NLP).
- Artificial Intelligence.
- Computational Intelligence.
- Machine Learning.
- Python.
- Data Science.
- Local Subjects:
- Natural Language Processing (NLP).
- Artificial Intelligence.
- Computational Intelligence.
- Machine Learning.
- Python.
- Data Science.
- Physical Description:
- 1 online resource (454 pages)
- Edition:
- 1st ed. 2024.
- Place of Publication:
- Springer Nature 2023
- Summary:
- 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.
- Contents:
- 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).
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 981-9919-99-1
- OCLC:
- 1409676679
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