Data-Driven Science and Engineering

Machine Learning, Dynamical Systems, and Control

Nonfiction, Science & Nature, Mathematics, Computers, General Computing, Technology
Cover of the book Data-Driven Science and Engineering by Steven L. Brunton, J. Nathan Kutz, Cambridge University Press
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Author: Steven L. Brunton, J. Nathan Kutz ISBN: 9781108386586
Publisher: Cambridge University Press Publication: February 28, 2019
Imprint: Cambridge University Press Language: English
Author: Steven L. Brunton, J. Nathan Kutz
ISBN: 9781108386586
Publisher: Cambridge University Press
Publication: February 28, 2019
Imprint: Cambridge University Press
Language: English

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.

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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.

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