Machine learning refined : foundations, algorithms, and applications / Jeremy Watt, Reza Borhani, and Aggelos Katsaggelos

By:

Watt, Jeremy

Contributor(s):

Material type:

TextPublication details: Cambridge : Cambridge University Press, 2016Description: 286 pISBN:

9781107123526 (hardback)

Subject(s):

Machine learning

DDC classification:

006.31 23 WAT-M

Summary: "Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization"--

Item type:

Books

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Current library	Call number	Status	Date due	Barcode
UMT Main Campus	006.31 WAT-M (Browse shelf(Opens below))	Checked out	2025-02-22	106452

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Previous	006.31 THE-M Machine learning : a Bayesian and optimization perspective /	006.31 THE-M Machine learning : from the classics to deep networks, transformers, and diffusion models /	006.31 VER-S Supervised learning with Python :	006.31 WAT-M Machine learning refined :	006.31 ZAC-D Pro deep learning with tensorflow :	006.312 ADV- Advances in knowledge discovery and management /	006.312 ART- Artificial intelligence using federated learning : fundamentals, challenges, and applications /	Next

"Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization"--

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