Data - Driven Science and Engineering : Machine Learning, Dynamical Systems, and Control / by S. L. Brunton and J. N. Kutz. [Electronic Resource]
Material type: Computer filePublication details: Cambridge : Cambridge University Press, 2019Description: xxii, 472pISBN:- 9781108380690
- 620.00285 B838D
Item type | Home library | Collection | Call number | Status | Notes | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|---|---|
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 |
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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