Data-Driven Science and Engineering - Machine Learning, Dynamical Systems, and Control (Hardcover)

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.

General

Imprint:	Cambridge UniversityPress
Country of origin:	United Kingdom
Release date:	February 2019
Authors:	Steven L. Brunton • J. Nathan Kutz
Dimensions:	261 x 184 x 24mm (L x W x T)
Format:	Hardcover
Pages:	492
ISBN-13:	978-1-108-42209-3
Categories:	Books > Professional & Technical > Technology: general issues > Engineering: general Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Optimization > General Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics
LSN:	1-108-42209-8
Barcode:	9781108422093

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