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

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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 highligh...

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Main Authors:
Brunton, Steven L., Kutz, Jose Nathan
Format:
Electronic eBook
Language:
English
Published:
Cambridge : Cambridge University Press, 2019.
Summary:
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.
Physical Description:
1 online resource (xxii, 472 pages) : digital, PDF file(s).
Notes:
Title from publisher's bibliographic system (viewed on 20 Feb 2019).
ISBN:
9781108380690 (ebook)
DOI:
10.1017/9781108380690
Subjects:
Engineering > Data processing.
Science > Data processing.
Mathematical analysis.
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