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Linear algebra and optimization with...

Gallier, Jean H.,

Linear algebra and optimization with applications to machine learning /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Linear algebra and optimization with applications to machine learning /Jean Gallier, Jocelyn Quaintance.
作者:	Gallier, Jean H.,
其他作者:	Quaintance, Jocelyn,
面頁冊數:	volume :illustrations (some color) ;24 cm
標題:	Algebras, Linear.
ISBN:	9789811206399

Linear algebra and optimization with applications to machine learning /
Gallier, Jean H.,

Linear algebra and optimization with applications to machine learning /Jean Gallier, Jocelyn Quaintance. - volume :illustrations (some color) ;24 cm

Includes bibliographical references and index.

Volume I. Linear algebra for computer vision, robotics, and machine learning -- Volume II. Fundamentals of optimization theory with applications to machine learning

"This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields"--

ISBN: 9789811206399

Standard No.: cam 22003618i 4500

LCCN: 2020001727Subjects--Topical Terms:

183087
Algebras, Linear.

LC Class. No.: QA184.2 / .G35 2020

Dewey Class. No.: 512/.5

Linear algebra and optimization with applications to machine learning /
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520 $a "This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields"-- $c Provided by publisher.
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