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Jun 26, 2024 · Discover Machine Learning Refined, 2nd Edition, Jeremy Watt, HB ISBN: 9781108480727 on Higher Education from Cambridge.
- Jeremy Watt, Reza Borhani, Aggelos K. Katsaggelos
- 2016
This book covers various essential machine learning methods (e.g., regression, classification, clustering, dimensionality reduction, and deep learning) from a unified mathematical perspective of seeking the optimal model parameters that minimize a cost function.
- Education
- Biography
- Research Interests
Ph.D. in Electrical Engineering, Northwestern University, Evanston, IL M.S. in Pure Mathematics, Indiana University, Bloomington, IN B.A. in Religious Studies, Indiana University, Bloomington, IN
Jeremy is a deep learning and machine learning researcher, developer, educator, and tinkerer with a wealth of experience building AI systems and helping others build them too. He has co-authored a university-level textbook on the subject called Machine Learning Refined(published by Cambridge University Press in 2016, much of which is available onli...
Machine learning, deep learning, computer vision, numerical optimization for large-scale machine learning
Jeremy Watt received his PhD in Computer Science and Electrical Engineering from Northwestern University. His research interests lie in machine learning and computer vision, as well as numerical optimization. Reza Borhani received his PhD in Computer Science and Electrical Engineering from Northwestern University.
Jan 9, 2020 · 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...
Jan 9, 2020 · Machine Learning Refined: Foundations, Algorithms, and Applications. Jeremy Watt, Reza Borhani, Aggelos Katsaggelos. Cambridge University Press, Jan 9, 2020 - Technology & Engineering. With its...
Sep 8, 2016 · Machine Learning Refined: Foundations, Algorithms, and Applications. Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous,...
