Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

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Published date July 28, 2022
Author Steven L. Brunton
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Description

Data driven discovery is revolutionizing how we model, predict. 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. 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. 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. chapter exercises. Online supplementary material including lecture videos per section, homeworks, data. code in MATLAB®, Python, Julia. R available on databookuw.com.

Specifications

FormatEPUB, PDF
Pages614
LanguageEnglish
ISBN-13978-1009098489

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Reviews

4.5★★★★★ 106
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J Joana K. Verified
★★★★★The diagrams do the teachingSeeing the concept drawn before the notation appears changed everything for me.
M Marcus T. Verified
★★★★★A set text for my classThe problem sets are graded properly and the solutions are complete.
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