Machine Learning for Engineers

Author:   Osvaldo Simeone (King's College London)
Publisher:   Cambridge University Press
Edition:   New edition
ISBN:  

9781316512821


Pages:   450
Publication Date:   03 November 2022
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Machine Learning for Engineers


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Overview

This self-contained introduction to machine learning, designed from the start with engineers in mind, will equip students with everything they need to start applying machine learning principles and algorithms to real-world engineering problems. With a consistent emphasis on the connections between estimation, detection, information theory, and optimization, it includes: an accessible overview of the relationships between machine learning and signal processing, providing a solid foundation for further study; clear explanations of the differences between state-of-the-art techniques and more classical methods, equipping students with all the understanding they need to make informed technique choices; demonstration of the links between information-theoretical concepts and their practical engineering relevance; reproducible examples using Matlab, enabling hands-on student experimentation. Assuming only a basic understanding of probability and linear algebra, and accompanied by lecture slides and solutions for instructors, this is the ideal introduction to machine learning for engineering students of all disciplines.

Full Product Details

Author:   Osvaldo Simeone (King's College London)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press
Edition:   New edition
Dimensions:   Width: 20.90cm , Height: 3.80cm , Length: 26.10cm
Weight:   1.470kg
ISBN:  

9781316512821


ISBN 10:   1316512827
Pages:   450
Publication Date:   03 November 2022
Audience:   General/trade ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Osvaldo Simeone is a Professor of Information Engineering at King's College London, where he directs King's Communications, Learning & Information Processing (KCLIP) lab. He is a Fellow of the IET and IEEE.

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