中图分类法:	TP181 版次：
著者:	Simeone, Osvaldo,
题名:	Machine learning for engineers : [ principles and algorithms through signal processing and information theory /] / ,
版次:	First edition.
出版发行:	出版地： Cambridge : 出版社： Cambridge University Press, 出版日期： 2022.
载体形态:	xxii, 578 pages : illustrations ; 25 cm
内容提要:	"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 : 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, and 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"--
主题词:	Engineering Data processing.
主题词:	Machine learning.