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Data-Driven Science and Engineering

Data-Driven Science and Engineering

Machine Learning, Dynamical Systems, and Control

by J. Nathan Kutz and Steven L. Brunton
Hardback
Publication Date: 31/03/2019

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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.
ISBN:
9781108422093
9781108422093
Category:
Mathematical theory of computation
Format:
Hardback
Publication Date:
31-03-2019
Publisher:
Cambridge University Press
Country of origin:
United Kingdom
Pages:
492
Dimensions (mm):
261x184x24mm
Weight:
1.19kg

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