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Machine learning refinedfoundations,...

Borhani, Reza.

Machine learning refinedfoundations, algorithms, and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning refinedJeremy Watt, Reza Borhani, and Aggelos K. Katsaggelos.
其他題名:	foundations, algorithms, and applications /
作者:	Watt, Jeremy.
其他作者:	Borhani, Reza.
出版者:	Cambridge :Cambridge University Press,2016.
面頁冊數:	xiii, 286 p. :ill., digital ;24 cm.
標題:	Machine learning.
電子資源:	https://doi.org/10.1017/CBO9781316402276
ISBN:	9781316402276$q(electronic bk.)

Machine learning refinedfoundations, algorithms, and applications /
Watt, Jeremy.

Machine learning refinedfoundations, algorithms, and applications /[electronic resource] :Jeremy Watt, Reza Borhani, and Aggelos K. Katsaggelos. - Cambridge :Cambridge University Press,2016. - xiii, 286 p. :ill., digital ;24 cm.

Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization.

ISBN: 9781316402276$q(electronic bk.)Subjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5 / .W38 2016

Dewey Class. No.: 006.31

Machine learning refinedfoundations, algorithms, and applications /
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520 $a Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization.
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