Machine Learning for Engineers
Author: Osvaldo Simeone (Author)
Publisher finelybook 出版社: Cambridge University Press
Publication Date 出版日期: 2022-11-20
Edition 版本: New
Language 语言: English
Print Length 页数: 450
ISBN-10: 1316512827
ISBN-13: 9781316512821
Book Description
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.
This self-contained introduction contains all students need to start applying machine learning principles to real-world engineering problems.
