bookCambridge University Press eBooksJan 31, 2019Closed access

Data-Driven Science and Engineering

University of Washington

Indexed incrossref

Abstract

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.

Citation impact

1,096
total citations
FWCI
49.73
Percentile
100%
References
513
Citations per year

Authors

2

Topics & keywords

Keywords
  • Data science
  • Applied science
  • Robotics
  • Computer science
  • Science and engineering
  • Range (aeronautics)
  • Autonomy
  • Graduate students
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