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Machine Learning Refined: Foundations, Algorithms, and...

Machine Learning Refined: Foundations, Algorithms, and Applications

Jeremy Watt, Reza Borhani, Aggelos Katsaggelos
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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.
年:
2020
出版:
Hardcover
出版社:
Cambridge University Press
语言:
english
页:
544
ISBN 10:
1108480721
ISBN 13:
9781108480727
文件:
PDF, 9.47 MB
IPFS:
CID , CID Blake2b
english, 2020
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