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

By:

Brunton, Steven L

Contributor(s):

Kutz, J. Nathan [Co-author]

Publication details: UK: Cambridge University Press, 2019.Description: xxii, 472p.: ill.; hbk.: 26cmISBN:

9781108422093

Subject(s):

DDC classification:

620.00285631 BRU

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. https://www.cambridge.org/in/universitypress/subjects/mathematics/computational-science/data-driven-science-and-engineering-machine-learning-dynamical-systems-and-control-2nd-edition?format=HB&isbn=9781009098489

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Books	IIT Gandhinagar	General	620.00285631 BRU (Browse shelf(Opens below))	1	Available		034300
Books	IIT Gandhinagar General Stacks	General	620.00285631 BRU (Browse shelf(Opens below))	1	Available		029595

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Includes bibliographical references and index.

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.

https://www.cambridge.org/in/universitypress/subjects/mathematics/computational-science/data-driven-science-and-engineering-machine-learning-dynamical-systems-and-control-2nd-edition?format=HB&isbn=9781009098489

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