東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Mathematical pictures at a data scie...

Foucart, Simon,

Linked to FindBook

Google Book

Amazon

博客來

Mathematical pictures at a data science exhibition /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Mathematical pictures at a data science exhibition // Simon Foucart.
Author:	Foucart, Simon,
Published:	Cambridge ;Cambridge University Press, : 2022.,
Description:	xx, 318 p. :ill. ;23 cm.
Subject:	Big data - Mathematics. -
ISBN:	9781009001854

Mathematical pictures at a data science exhibition /
Foucart, Simon,

Mathematical pictures at a data science exhibition /Simon Foucart. - Cambridge ;Cambridge University Press,2022. - xx, 318 p. :ill. ;23 cm.

Includes bibliographical references and index.

"In the past few decades, heuristic methods adopted by big techcompanies have complemented existing scientific disciplines to form the newfield of Data Science. This text provides deep and comprehensive coverage ofthe mathematical theory supporting the field. Composed of 27 lecture-lengthchapters with exercises, it embarks the readers on an engaging itinerarythrough key subjects in data science, including machine learning, optimalrecovery, compressive sensing (also known as compressed sensing),optimization, and neural networks. While standard material is covered, thebook also includes distinctive presentations of topics such as reproducing kernel Hilbert spaces, spectral clustering, optimal recovery, compressivesensing, group testing, and applications of semidefinite programming. Students and data scientists with less mathematical background willappreciate the appendices that supply more details on some of the abstract concepts"--

ISBN: 9781009001854GBP29.99

LCCN: 2022002178Subjects--Topical Terms:

2147694
Big data
--Mathematics.

LC Class. No.: QA76.9.B45 / F68 2022

Dewey Class. No.: 005.7

Mathematical pictures at a data science exhibition /
LDR:01608cam a2200205 a 450 001 2259164
005 20220314100205.0
008 220427s2022 enka b 001 0 eng
010 $a 2022002178
020 $a 9781009001854 $q (pbk.) : $c GBP29.99
020 $a 9781316518885 $q (hbk.)
040 $a LBSOR/DLC $b eng $c DLC
042 $a pcc
050 0 0 $a QA76.9.B45 $b F68 2022
082 0 0 $a 005.7 $2 23
084 $a COM000000 $2 bisacsh
100 1 $a Foucart, Simon, $e author. $3 3565420
245 1 0 $a Mathematical pictures at a data science exhibition / $c Simon Foucart.
260 # $a Cambridge ; $a New York, NY : $b Cambridge University Press, $c 2022.
300 $a xx, 318 p. : $b ill. ; $c 23 cm.
504 $a Includes bibliographical references and index.
520 # $a "In the past few decades, heuristic methods adopted by big techcompanies have complemented existing scientific disciplines to form the newfield of Data Science. This text provides deep and comprehensive coverage ofthe mathematical theory supporting the field. Composed of 27 lecture-lengthchapters with exercises, it embarks the readers on an engaging itinerarythrough key subjects in data science, including machine learning, optimalrecovery, compressive sensing (also known as compressed sensing),optimization, and neural networks. While standard material is covered, thebook also includes distinctive presentations of topics such as reproducing kernel Hilbert spaces, spectral clustering, optimal recovery, compressivesensing, group testing, and applications of semidefinite programming. Students and data scientists with less mathematical background willappreciate the appendices that supply more details on some of the abstract concepts"-- $c Provided by publisher.
650 # 0 $a Big data $x Mathematics. $3 2147694
650 # 0 $a Computer science $x Mathematics. $3 532725
650 # 0 $a Information science $x Mathematics. $3 3565421