Ruye Wang (2026) Introduction to Machine Learning. From Math to Code. Cambridge University Press, Cambridge, UK. ISBN 9781316519509.

Condition: New, few nicks on the hardcover.

Introduction to Machine Learning
Emphasizing how and why machine learning algorithms work, this
introductory textbook bridges the gap between the theoretical foundations
of machine learning and its practical algorithmic and code-level
implementation.
Key features
• Over 85 thorough worked examples inMATLAB®, demonstrating how
algorithms are implemented and applied while illustrating their results.
• In-depth coverage of essential mathematics including multivariable calculus,
linear algebra, probability and statistics, numerical methods, and
optimization.
• Over 75 end-of-chapter problems empower students to develop their own
code to implement the algorithms presented, equipping themwith handson
experience.
• Presents samples of essential MATLAB code, demonstrating how a
mathematical idea is converted from equations to code, and providing
a jumping-off point for students.
Accompanied online by instructor lecture slides and additional appendices,
this is an excellent introduction to machine learning for senior
undergraduate and graduate students in engineering and computer science.
Ruye Wang is an Emeritus Professor of Engineering at Harvey Mudd College,
with over 30 years of experience in teaching courses in engineering and
computer science. Previously a principal investigator at the Jet Propulsion
Laboratory, NASA, his research interests include image processing, computer
vision, machine learning, and remote sensing. He is the author of the
textbook Introduction to Orthogonal Transforms (2012).