000			01771 a2200217 4500
003			OSt
020			_a9781009098489
040			_cIIT Kanpur
041			_aeng
082			_a620.00285 _bB838d2
100			_aBrunton, Steven L.
245			_aData-driven science and engineering [2nd ed.] _bmachine learning, dynamical systems, and control _cSteven L. Brunton and J. Nathan Kutz
250			_a2nd ed.
260			_bCambridge University Press _c2022 _aCambridge
300			_axxiv, 590p
520			_a"Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering a broad overview of the growing intersection of data-driven methods, machine learning, applied optimization, and classical fields of engineering mathematics and mathematical physics. With a focus on integrating dynamical systems modeling and control with modern methods in applied machine learning, this text includes methods that were chosen for their relevance, simplicity, and generality. Topics range from introductory to research-level material, making it accessible to advanced undergraduate and beginning graduate students from the engineering and physical sciences. The second edition features new chapters on reinforcement learning and physics-informed machine learning, significant new sections throughout, and chapter exercises. Online supplementary material including lecture videos per section, homeworks, data, and codes in MATLAB, Python, and Julia available on databookuw.com"
650			_aEngineering -- Data processing
650			_aScience -- Data processing
700			_aKutz, J. Nathan
942			_cBK
999			_c567409 _d567409