01338nam a22002057a 4500 12348 12348 230427b 2022 ||||| |||| 00| 0 eng d 9781009098489 620.0028 BRU Brunton, Steven Data-driven science and engineering : machine learning, dynamical systems, and control 2nd ed. UK CAMBRIDGE UNIVERSITY PRESS 2022 xxiv, 590p. Data-driven discovery is revolutionizing the modelling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modelling 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. Sparsity and compressed sensing Reinforcement Learning Linear Control Theory Kutz, J. Nathan Co-author BK 0 0 ddc 0 620_002800000000000_BRU 0 NFIC 15458 MU MU GEN 2023-04-27 1 620.0028 BRU MPC6651 2025-03-17 2024-08-02 BK Column - 24