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

By: Contributor(s): Material type: TextTextPublisher: New York : Cambridge University Press, 2016Description: xiii, 286 pages : illustrations ; 26 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781107123526
Subject(s): DDC classification:
  • 006.31 WAT 2016 23
LOC classification:
  • Q325.5 .W38 2016
Online resources: 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"-- Provided by publisher.
List(s) this item appears in: eBooks_FEC
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Holdings
Item type Current library Home library Call number Status Date due Barcode Item holds
Electronic Book Electronic Book FIRST CITY UNIVERSITY COLLEGE FIRST CITY UNIVERSITY COLLEGE 006.31 WAT 2016 (Browse shelf(Opens below)) e-book e00065
Total holds: 0

"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"-- Provided by publisher.