東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

FindBook

Google Book

Amazon

博客來

Natural language processing = a textbook with Python implementation /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Natural language processing/ by Raymond S. T. Lee.
其他題名:	a textbook with Python implementation /
作者:	Lee, Raymond S. T.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	xxxii, 437 p. :ill., digital ;24 cm.
內容註:	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 (Hour 11-12) -- Chapter 16. Workshop#7 - Building Chatbot with TensorFlow and Transformer Technology (Hour 13-14)
Contained By:	Springer Nature eBook
標題:	Natural language processing (Computer science) -
電子資源:	https://doi.org/10.1007/978-981-99-1999-4
ISBN:	9789819919994

Natural language processing = a textbook with Python implementation /
Lee, Raymond S. T.

Natural language processinga textbook with Python implementation /[electronic resource] :by Raymond S. T. Lee. - Singapore :Springer Nature Singapore :2024. - xxxii, 437 p. :ill., digital ;24 cm.

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 (Hour 11-12) -- Chapter 16. Workshop#7 - Building Chatbot with TensorFlow and Transformer Technology (Hour 13-14)

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.

ISBN: 9789819919994

Standard No.: 10.1007/978-981-99-1999-4doiSubjects--Topical Terms:

565309
Natural language processing (Computer science)

LC Class. No.: QA76.9.N38

Dewey Class. No.: 006.35

Natural language processing = a textbook with Python implementation /
LDR:03133nmm a2200325 a 4500 001 2367538
003 DE-He213
005 20231114103438.0
006 m d
007 cr nn 008maaau
008 241127s2024 si s 0 eng d
020 $a 9789819919994 $q (electronic bk.)
020 $a 9789819919987 $q (paper)
024 7 $a 10.1007/978-981-99-1999-4 $2 doi
035 $a 978-981-99-1999-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.N38
072 7 $a UYQL $2 bicssc
072 7 $a COM073000 $2 bisacsh
072 7 $a UYQL $2 thema
082 0 4 $a 006.35 $2 23
090 $a QA76.9.N38 $b L479 2024
100 1 $a Lee, Raymond S. T. $3 3445112
245 1 0 $a Natural language processing $h [electronic resource] : $b a textbook with Python implementation / $c by Raymond S. T. Lee.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2024.
300 $a xxxii, 437 p. : $b ill., digital ; $c 24 cm.
505 0 $a 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 (Hour 11-12) -- Chapter 16. Workshop#7 - Building Chatbot with TensorFlow and Transformer Technology (Hour 13-14)
520 $a 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.
650 0 $a Natural language processing (Computer science) $3 565309
650 0 $a Python (Computer program language) $3 729789
650 1 4 $a Natural Language Processing (NLP) $3 3381674
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Python. $3 3201289
650 2 4 $a Data Science. $3 3538937
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-99-1999-4
950 $a Computer Science (SpringerNature-11645)