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[null,"1.","Record Nr.",null,"UNINA9910763593503321"]
[null,null,"Autore",null,"Lee Raymond S. T"]
[null,null,"Titolo",null,"Natural Language Processing : A Textbook with Python Implementation / / by Raymond S. T. Lee"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"981-9919-99-1"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (454 pages)"]
[null,null,"Disciplina",null,"006.35"]
[null,null,"Soggetti",null,"Natural language processing (Computer science)"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computational intelligence"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Python (Computer program language)"]
[{"$nulls":4},"Artificial intelligence - Data processing"]
[{"$nulls":4},"Natural Language Processing (NLP)"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Python"]
[{"$nulls":4},"Data Science"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Part I – Concepts and Technology -- Chapter 1. Introduction to Natural Language Processing -- Chapter 2. N-gram Language Model -- Chapter 3. Part-of-Speech Tagging -- Chapter 4. Syntax and Parsing -- Chapter 5. Meaning Representation -- Chapter 6. Semantic Analysis -- Chapter 7. Pragmatic Analysis and Discourse -- Chapter 8. Transfer Learning and Transformer Technology -- Chapter 9. Major Natural Language Processing Applications -- Part II –Natural Language Processing Workshops with Python Implementation in 14 Hours -- Chapter 10. Workshop#1 – Basics of Natural Language Toolkit (Hour 1-2) -- Chapter 11. Workshop#2 – N-grams Modeling with Natural Language Toolkit (Hour 3-4) -- Chapter 12. Workshop#3 – Part-of-Speech Tagging using Natural Language Toolkit (Hour 5-6) -- Chapter 13. Workshop#4 – Semantic Analysis and Word Vectors using spaCy (Hour 7-8) -- Chapter 14. Workshop#5 – Sentiment Analysis and Text "]
[{"$nulls":4},"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)."]
[null,null,null,"Sommario/riassunto","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."]