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Natural language processing : a mach...

Teng, Zhiyang.

Natural language processing : a machine learning perspective

紀錄類型:	書目-語言資料,印刷品 : 單行本
副題名:	a machine learning perspective
作者:	ZhangYue.,
其他作者:	TengZhiyang.,
出版地:	Cambridge
出版者:	Cambridge University Press;
出版年:	2021.
面頁冊數:	xvi, 470 p.ill. : 26 cm.;
標題:	Natural language processing (Computer science) -
標題:	Machine learning. -
標題:	Machine learning. -
標題:	Natural language processing (Computer science) -
摘要註:	With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an online resource, this textbook is an invaluable tool for the upper undergraduate and graduate student.
ISBN:	9781108420211

Natural language processing : a machine learning perspective
Zhang, Yue.

Natural language processing : a machine learning perspective / Yue Zhang, Zhiyang Teng. - Cambridge : Cambridge University Press, 2021.. - xvi, 470 p. ; ill. ; 26 cm..
Includes bibliographical references (p. 453-467) and index..
ISBN 9781108420211
Natural language processing (Computer science)Machine learning.Machine learning.Natural language processing (Computer science)

Teng, Zhiyang.

Natural language processing : a machine learning perspective
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330 $a With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an online resource, this textbook is an invaluable tool for the upper undergraduate and graduate student.
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