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Machine Learning for Fluid Mechanics

Steve Brunton via YouTube

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This high-level course surveys how machine learning is applied to fluid mechanics using examples of pattern extraction, reduced-order models, closure modeling, superresolution, and flow control.

Syllabus

Introduction
What is Machine Learning
Machine Learning is not Magic
History of Machine Learning
AI Winter
Patterns
orthogonal decomposition
lowdimensional patterns
boundary layer simulations
turbulent energy cascade
closure modeling
superresolution
autoencoders
reduced order models
flow control
inspiration from biology

Taught by

Steve Brunton

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