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

Brunton, Steven L.; J. Nathan Kutz

ISBN 10: 1108422098 / ISBN 13: 9781108422093

Editore: Cambridge University Press, 2019

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Dati bibliografici

Titolo: Data-Driven Science and Engineering: Machine...

Casa editrice: Cambridge University Press

Data di pubblicazione: 2019

Legatura: Hardcover

Condizione: Very Good

Edizione: 1st Edition

Descrizione articolo

Riassunto:

This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.

Informazioni sugli autori:

Steven L. Brunton is Associate Professor of Mechanical Engineering at the University of Washington. He is also Adjunct Associate Professor of Applied Mathematics and a Data-Science Fellow at the eScience Institute. His research applies data science and machine learning for dynamical systems and control to fluid dynamics, biolocomotion, optics, energy systems, and manufacturing. He has co-authored two textbooks, received the Army and Air Force Young Investigator awards, and was awarded the University of Washington College of Education teaching award.

J. Nathan Kutz is the Robert Bolles and Yasuko Endo Professor of Applied Mathematics at the University of Washington, and served as department chair until 2015. He is also Adjunct Professor of Electrical Engineering and Physics and a Senior Data-Science Fellow at the eScience Institute. His research interests are in complex systems and data analysis where machine learning can be integrated with dynamical systems and control for a diverse set of applications. He is an author of two textbooks and has received the Applied Mathematics Boeing Award of Excellence in Teaching and an NSF CAREER award.