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Data-driven science and engineering ...

Brunton, Steven L. (1984-)

Data-driven science and engineering :machine learning, dynamical systems, and control /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Data-driven science and engineering :Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington.
Reminder of title:	machine learning, dynamical systems, and control /
Author:	Brunton, Steven L.
other author:	Kutz, Jose Nathan,
Description:	xxii, 472 pages :some color illustrations ;27 cm
Subject:	EngineeringData processing.
ISBN:	9781108422093$q(hardcover ;

Data-driven science and engineering :machine learning, dynamical systems, and control /
Brunton, Steven L.1984-

Data-driven science and engineering :machine learning, dynamical systems, and control /Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington. - xxii, 472 pages :some color illustrations ;27 cm

Includes bibliographical references and index.

"Data-driven discovery is revolutionizing the modelling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modelling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art"--

ISBN: 9781108422093$q(hardcover ;GBP$49.99

Standard No.: 40029110218

LCCN: 2018029888

Nat. Bib. No.: GBB914303bnb

Nat. Bib. Agency Control No.: 019220599UkSubjects--Topical Terms:

180008
Engineering
--Data processing.

LC Class. No.: TA330 / .B78 2019

Dewey Class. No.: 620.00285/631

Data-driven science and engineering :machine learning, dynamical systems, and control /
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020 $a 1108422098$q(hardcover ; $q alkaline paper)
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100 1 $a Brunton, Steven L. $q (Steven Lee), $d 1984- $e author. $3 857120
245 1 0 $a Data-driven science and engineering : $b machine learning, dynamical systems, and control / $c Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington.
264 1 $a Cambridge, United Kingdom ; $a New York, NY : $b Cambridge University Press, $c 2019.
264 4 $c ©2019
300 $a xxii, 472 pages : $b some color illustrations ; $c 27 cm
336 $a text $b txt $2 rdacontent
337 $a unmediated $b n $2 rdamedia
338 $a volume $b nc $2 rdacarrier
504 $a Includes bibliographical references and index.
520 $a "Data-driven discovery is revolutionizing the modelling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modelling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art"-- $c Provided by publisher.
650 0 $a Engineering $x Data processing. $3 180008
650 0 $a Science $x Data processing. $3 180009
650 0 $a Mathematical analysis. $3 186133
700 1 $a Kutz, Jose Nathan, $e author. $3 654035
994 $a C0 $b TWNUK