Machine Learning for Engineers by Osvaldo Simeone

Machine Learning for Engineers by Osvaldo Simeone

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.

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.

SKU	Unavailable
ISBN 13	9781316512821
ISBN 10	1316512827
Title	Machine Learning for Engineers
Author	Osvaldo Simeone
Condition	Unavailable
Publisher	Cambridge University Press
Year published	2022-11-03
Number of pages	450
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
Note	Unavailable