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Data - Driven Science and Engineering : Machine Learning, Dynamical Systems, and Control / by S. L. Brunton and J. N. Kutz. [Electronic Resource]

By: Material type: Computer fileComputer filePublication details: Cambridge : Cambridge University Press, 2019Description: xxii, 472pISBN:
  • 9781108380690
Related works:
  • Kutz, J. N. [Author]
Subject(s): DDC classification:
  • 620.00285 B838D
Online resources: 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.
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Holdings
Item type Home library Collection Call number Status Notes Date due Barcode Item holds
e-Book e-Book S. R. Ranganathan Learning Hub Online Textbook 620.00285 B838D (Browse shelf(Opens below)) Available (e-Book For Access) Platform : Cambridge Core EB0428
Total holds: 0

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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