Machine Learning Refined: Foundations, Algorithms, and Applications

Borhani, R. et al.

ISBN 10: 1107123526 / ISBN 13: 9781107123526

Edité par Cambridge University Press, 2017

A propos de cet article

This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In good all round condition. Dust jacket in good condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,850grams, ISBN:9781107123526. N° de réf. du vendeur 9860938

Détails bibliographiques

Titre : Machine Learning Refined: Foundations, ...

Éditeur : Cambridge University Press

Date d'édition : 2017

Reliure : Couverture rigide

Etat : Good

Etat de la jaquette : Jaquette

A propos de ce titre

Synopsis :

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.

À propos des auteurs:

Jeremy Watt received his PhD in Computer Science and Electrical Engineering from Northwestern University, Illinois. 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, Illinois. His research interests lie in the design and analysis of algorithms for problems in machine learning and computer vision.

Aggelos K. Katsaggelos is a professor and holder of the AT&T chair in the Department of Electrical Engineering and Computer Science at Northwestern University, Illinois, where he also heads the Image and Video Processing Laboratory.