Data-Driven Science and Engineering. Machine Learning, Dynamical Systems, and Control, 2 Revised edition, Hardback

Data-driven discovery is revolutionizing how we model, predict, and control complex systems. This text integrates emerging machine learning and data science methods for engineering and science communities. Now with Python and MATLAB (R), new chapters on reinforcement learning and physics-informed machine learning, and supplementary videos and code.

• Publisher: Cambridge University Press
• Author(s): J. Nathan (University of Washington) Kutz
• Illustration(s): Worked examples or Exercises
• Number of pages: 614
• Publication date: 2022
• Dimensions: 185 x 261 x 33
• Cover type: Hardback