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Inference and Learning from Data: Volume 3 : Learning

By: (Author) Ali H. Sayed

Manufactured on Demand
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Ksh 15,500.00

Format: Hardback or Cased Book

ISBN-10: 100921828X

ISBN-13: 9781009218283

Publisher: Cambridge University Press

Imprint: Cambridge University Press

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Dec 22nd, 2022

Print length: 990 Pages

Weight: 1,744 grams

Dimensions (height x width x thickness): 14.70 x 25.20 x 4.30 cms

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Written in an engaging and rigorous style by a world authority in the field, this is an accessible and comprehensive introduction to learning methods. With downloadable Matlab code and solutions for instructors, this is the ideal introduction for students of data science, machine learning and engineering.
This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This final volume, Learning, builds on the foundational topics established in volume I to provide a thorough introduction to learning methods, addressing techniques such as least-squares methods, regularization, online learning, kernel methods, feedforward and recurrent neural networks, meta-learning, and adversarial attacks. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including complete solutions for instructors), 280 figures, 100 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Inference, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, data and inference.

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