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Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control (Second Edition) by Steven L. Brunton and J. Nathan Kutz is a cutting-edge textbook that merges advanced mathematical methods with modern data science. The text covers essential computational concepts from machine learning algorithms and system identification to reduced-order modeling and control theory, providing a robust engineering framework for analyzing complex, high-dimensional dynamical systems.
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