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Data-Driven Science and Engineering: Machine Learning,...

Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

Steven L. Brunton, J. Nathan Kutz
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Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling 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.
种类:
年:
2019
出版社:
Cambridge University Press
语言:
english
页:
472
ISBN 10:
1108422098
ISBN 13:
9781108422093
文件:
PDF, 72.73 MB
IPFS:
CID , CID Blake2b
english, 2019
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