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

"This is a very timely, comprehensive, and well written book in what is now one of the most dynamic and impactful areas of modem applied mathematics. Data science is rapidly taking center stage in our society. The subject cannot be ignored, either by domain scientists or by researchers in applied mathematics who intend to develop algorithms that the community will use. The book by Brunton and Katz is an excellent text for a beginning graduate student, or even for a more advanced researcher interested in this field.
The main theme seems to be applied optimization. The subtopics include dimensional reduction, machine learning, dynamics and control, and reduced-order methods. These were well chosen and well covered." - Stanley Osher, University of California. "Professors Kutz and Brunton bring both passion and rigor to this most timely subject matter. Data analytics is the important topic for engineering in the twenty-first century, and this book covers the far-reaching subject matter with clarity and code examples.
Bravo ! " - Steve M. Legensky, Founder and General Manager, Intelligent Light. "Brunton and Kutz provide a lively and comprehensive treatise on machine learning and data-mining algorithms as applied to physical systems arising in science and engineering and their control. They provide an abundance of examples and wisdom that will be of great value to students and practitioners alike." - Tim Colonias, California Institute of Technology.
Steven L. Brunton is Associate Professor of Mechanical Engineering at the University of Washington. He is also Adjunct Associate Professor of Applied Mathematics and 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 is an author of two textbooks, received the Army and Air Force Young Investigator awards, and was awarded the University of Washington College of Education teaching award.