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.
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Product Details
Weight: 1360g
Dimensions: 183 x 255mm
Publication Date: 09 Jan 2020
Publisher: Cambridge University Press
Publication City/Country: United Kingdom
Language: English
ISBN13: 9781108480727
About Aggelos K. KatsaggelosJeremy WattReza Borhani
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).