000			01591nam a22002177a 4500
999			_c1528 _d1528
005			20220405112022.0
008			220405b ||||| |||| 00| 0 eng d
020			_a9781108422093
082			_a620.002 _bBRU
100			_a Brunton, Steven L.
245			_aData-driven science and engineering : _bmachine learning, dynamical systems, and control _cSteven L. Brunton, J. Nathan Kutz
260			_a New York, NY : _bCambridge University Press, 2019. _c©2019
300			_a472P:
505			_tPart I -- Dimensionality Reduction and Transforms - _tPart II -- Machine Learning and Data Analysis _tPart III -- Dynamics and Control - _tPart IV -- Reduced Order Models -
520			_a 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
650			_a Engineering -- Data processing.
650			_aMathematical analysis.
650			_aScience -- Data processing.
700			_a Kutz, Jose Nathan
942			_2ddc _cBK