Natural Language Processing (English, Raymond S. T. Lee)
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Specifications
| Publisher | Springer |
| Language | English |
| ISBN-13 | 9789819919987 |
| ISBN-10 | 9819919983 |
| Author | Raymond S. T. Lee |
Product Description
About the Book
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 te…
ISBN: 9789819919987
Book Insights
What You'll Learn
- ·In-depth exploration of topics covered in Natural Language Processing
- ·Key concepts explained with clarity and practical examples
- ·Insights valuable for anyone studying or working in Springer
Who Should Read This
Students at the undergraduate and postgraduate level, as well as educators.
Key Highlights
- ·Brand new physical book delivered across India
- ·15-day hassle-free return policy
Customer Reviews
A great starting point to learn NLP concepts and implementation in Python
I'm a college lecturer planning a new course on NLP next semester and am looking for a textbook to teach the course with. I have referred to several NLP textbooks and Python NLP toolbooks, and most of them either focus too much on the concepts and theories of computational linguistics, or focus too much on the practicality of Python implementation, without any explanation of NLP concepts. As mentioned on the book cover, this book is the one that strikes the best balance between basic NLP concept
Very useful and practical NLP book
I have read several NLP books, this one is the best cover both basic NLP concepts and knowledge , together with step-by-step Python workshop for the building of NLP application.Part I - NLP ConceptsChapter 1 – Introduction to NLPChapter 2 – N-gram Language ModelChapter 3 – Part-of-Speech TaggingChapter 4 – Syntax and ParsingChapter 5 – Meaning RepresentationChapter 6 – Semantic AnalysisChapter 7 – Pragmatic AnalysisChapter 8 – Transfer Learning and Transformer Technology Chapter 9 – Major NLP Ap
