02023cam a22003618i 4500
20552686
OSt
20210518113515.0
180622s2019 enk b 001 0 eng
2018029888
9781108422093 (hardback : alk. paper)
DLC
eng
rda
DLC
pcc
TA330
.B78 2019
8870
23
TA 330 .B78 2019
Brunton, Steven L.
(Steven Lee),
1984-
author.
Data-driven science and engineering :
machine learning, dynamical systems, and control /
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington.
1809
Cambridge :
Cambridge University Press,
2019.
pages cm
text
txt
rdacontent
unmediated
n
rdamedia
volume
nc
rdacarrier
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"--
Provided by publisher.
Engineering
Data processing.
Science
Data processing.
Mathematical analysis.
Kutz, Jose Nathan,
author.
7
cbc
orignew
1
ecip
20
y-gencatlg
ddc
BK
rk21 2018-06-22
rk21 2018-06-22 to rk09 for review
10296
10296
8870
2021-05-18
2021-05-18
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2021-05-18
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TA 330 .B78 2019
TA 330 .B78 2019
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ddc
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BK
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0
9680
2021-05-18
EUL
2021-05-18
8871
2021-05-18
8872
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TA 330 .B78 2019