
Data-Driven Science and Engineering
Machine Learning, Dynamical Systems, and Control
- English
- PDF
- Available on iOS & Android
Data-Driven Science and Engineering
Machine Learning, Dynamical Systems, and Control
About this book
Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art.
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Information
Table of contents
- Cover
- Half-Title
- Title page
- Copyright Information
- Contents
- Preface
- Common Optimization Techniques, Equations, Symbols, and Acronyms
- Part I Dimensionality Reduction and Transforms
- Part II Machine Learning and Data Analysis
- Part III Dynamics and Control
- Part IV Reduced Order Models
- Glossary
- Bibliography
- Index
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