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Linear algebra and optimization with...

Gallier, Jean H.

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Linear algebra and optimization with applications to machine learning.. Vol.1,. linear algebra for computer vision, robotics, and machine learning /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Linear algebra and optimization with applications to machine learning./ Jean Gallier, Jocelyn Quaintance.
Author:	Gallier, Jean H.
other author:	Quaintance, Jocelyn.
Published:	Singapore :World Scientific Publishing Co. Pte. Ltd., : c2020.,
Description:	xv, 806 p. :ill. (some col.) ;23 cm.
Subject:	Algebras, Linear - Data processing. -
ISBN:	9789811206399

Linear algebra and optimization with applications to machine learning.. Vol.1,. linear algebra for computer vision, robotics, and machine learning /
Gallier, Jean H.

Linear algebra and optimization with applications to machine learning.Vol.1,linear algebra for computer vision, robotics, and machine learning /Jean Gallier, Jocelyn Quaintance. - Singapore :World Scientific Publishing Co. Pte. Ltd.,c2020. - xv, 806 p. :ill. (some col.) ;23 cm.

Includes bibliographical references (p.791-794) and index.

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: 9789811206399US198.00Subjects--Topical Terms:

533876
Algebras, Linear
--Data processing.

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

Dewey Class. No.: 512/.5

Linear algebra and optimization with applications to machine learning.. Vol.1,. linear algebra for computer vision, robotics, and machine learning /
LDR:01638cam a2200229 a 4500 001 2224759
003 OCoLC
005 20200506214413.0
008 210125s2020 si a b 001 0 eng d
020 $a 9789811206399 $q (v.1 : $q hbk.) : $c US198.00
020 $a 9811206392 $q (v.1 : $q hbk.)
020 $a 9789811207716 $q (v.1 : $q pbk.)
020 $a 9811207712 $q (v.1 : $q pbk.)
040 $a YDX $b eng $e aacr2 $c YDX $d UV1 $d YDXIT $d CKT $d NCU
041 0 # $a eng
042 $a nbic
050 0 0 $a QA184.2 $b .G35 2020
082 0 0 $a 512/.5 $2 23
100 1 $a Gallier, Jean H. $3 540196
245 1 0 $a Linear algebra and optimization with applications to machine learning. $n Vol.1, $p linear algebra for computer vision, robotics, and machine learning / $c Jean Gallier, Jocelyn Quaintance.
260 # $a Singapore : $b World Scientific Publishing Co. Pte. Ltd., $c c2020.
300 $a xv, 806 p. : $b ill. (some col.) ; $c 23 cm.
504 $a Includes bibliographical references (p.791-794) and index.
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.
650 # 0 $a Algebras, Linear $x Data processing. $3 533876
650 # 0 $a Computer science $x Mathematics. $3 532725
650 # 0 $a Computer-aided design. $3 531217
650 # 0 $a Robotics. $3 519753
700 1 # $a Quaintance, Jocelyn. $3 3470124