Machine Learning Refined: Foundations, Algorithms, and Applications

Watt, Jeremy,Borhani, Reza,Katsaggelos, Aggelos K.

ISBN 10: 1108480721 / ISBN 13: 9781108480727

Published by Cambridge University Press, 2020

About this Item

Cover and edges may have some wear. Loose binding, good reading copy.

Seller Inventory # mon0003858905

Bibliographic Details

• Title: Machine Learning Refined: Foundations, Algorithms, and Applications
• Publisher: Cambridge University Press
• Publication Date: 2020
• Language: English
• ISBN 10: 1108480721
• ISBN 13: 9781108480727
• Binding: hardcover
• Edition: 2nd Edition
• Condition: Acceptable

About this title

Synopsis

With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.

About the Authors

Jeremy Watt received his Ph.D. in Electrical Engineering from Northwestern University, Illinois, and is now a machine learning consultant and educator. He teaches machine learning, deep learning, mathematical optimization, and reinforcement learning at Northwestern University, Illinois.

Reza Borhani received his Ph.D. in Electrical Engineering from Northwestern University, Illinois, and is now a machine learning consultant and educator. He teaches a variety of courses in machine learning and deep learning at Northwestern University, Illinois.

Aggelos K. Katsaggelos is the Joseph Cummings Professor at Northwestern University, Illinois, where he heads the Image and Video Processing Laboratory. He is a Fellow of Institute of Electrical and Electronics Engineers (IEEE), SPIE, the European Association for Signal Processing (EURASIP), and The Optical Society (OSA) and the recipient of the IEEE Third Millennium Medal (2000).