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Machine Learning Refined Foundations, Algorithms, and Applications

Authors

Jeremy Watt
, Northwestern University, Illinois,
Reza Borhani
, Northwestern University, Illinois,
Aggelos K. Katsaggelos
, Northwestern University, Illinois
Published 2020

Description

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…

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Key features

  • Encourages geometric intuition and algorithmic thinking to provide an intuitive understanding of key concepts and an interactive way of learning
  • Features coding exercises for Python to help put knowledge into practice
  • Emphasizes practical applications, with real-world examples, to give students the confidence to conduct research, build products, and solve problems
  • Completely self-contained, with appendices covering the essential mathematical prerequisites

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