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020 _a9789819919994
024 7 _a10.1007/978-981-99-1999-4
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
050 0 4 _aQA76.9.N38
_b2024
100 1 _aLee, Raymond S. T.
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 0 0 _aNatural Language Processing
_b: A Textbook with Python Implementation
_cby Raymond S T Lee
250 _afirst edition 2024
264 1 _aSingapore
_c2024
_bSpringer International Publishing
300 _a1 recurso en línea
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
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347 _atext file
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505 0 _aPart 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 (Hour 11-12) -- Chapter 16. Workshop#7 - Building Chatbot with TensorFlow and Transformer Technology (Hour 13-14).
520 _aThis 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.
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-99-1999-4
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
912 _aZDB-2-SCS
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