Articles liés à Introduction to Machine Learning: From Math to Code

Introduction to Machine Learning: From Math to Code - Couverture rigide

Wang, Ruye

 
9781316519509: Introduction to Machine Learning: From Math to Code
Couverture rigide
ISBN 10 : 1316519503 ISBN 13 : 9781316519509
Editeur : Cambridge University Press, 2025

Synopsis

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. Over 85 thorough worked examples, in both Matlab and Python, demonstrate how algorithms are implemented and applied whilst illustrating the end result. Over 75 end-of-chapter problems empower students to develop their own code to implement these algorithms, equipping them with hands-on experience. Matlab coding examples demonstrate how a mathematical idea is converted from equations to code, and provide a jumping off point for students, supported by in-depth coverage of essential mathematics including multivariable calculus, linear algebra, probability and statistics, numerical methods, and optimization. Accompanied online by instructor lecture slides, downloadable Python code and additional appendices, this is an excellent introduction to machine learning for senior undergraduate and graduate students in Engineering and Computer Science.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l'auteur

Ruye Wang is an Emeritus Professor of Engineering at Harvey Mudd College, with over thirty 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).

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Cambridge University Press
Date d'édition
2025
Langue
anglais
ISBN 10 
1316519503
ISBN 13 
9781316519509
Reliure
Relié
Nombre de pages
578
Coordonnées du fabricant
Cambridge University Press
https://www.cambridge.org/

Via Honduras,15
Pomezia
Italia
71
Italie