Cambridge University Press is pleased to announce the upcoming publication of
Data-Driven Fluid Mechanics: Combining First Principles and Machine Learning edited by Miguel A. Mendez, Andrea Ianiro, Bernd R. Noack, and Steven L. Brunton.
Big data and machine learning are driving profound technological progress across nearly every industry, and are rapidly shaping fluid mechanics research. This is a self-contained and pedagogical treatment of the data-driven tools that are leading research in model-order reduction, system identification, flow control, and turbulence closures.
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