‏303.00 ₪

Data-Driven Science and Engineering

‏303.00 ₪
ISBN13
9781108422093
יצא לאור ב
New York
עמודים
500
פורמט
Hardback
תאריך יציאה לאור
28 בפבר׳ 2019
This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.
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.
מידע נוסף
עמודים 500
פורמט Hardback
ISBN10 1108422098
יצא לאור ב New York
תאריך יציאה לאור 28 בפבר׳ 2019
תוכן עניינים Part I. Dimensionality Reduction and Transforms: 1. Singular value decomposition; 2. Fourier and wavelet transforms; 3. Sparsity and compressed sensing; Part II. Machine Learning and Data Analysis: 4. Regression and model selection; 5. Clustering and classification; 6. Neural networks and deep learning; Part III. Dynamics and Control: 7. Data-driven dynamical systems; 8. Linear control theory; 9. Balanced models for control; 10. Data-driven control; Part IV. Reduced-Order Models: 11. Reduced-order models (ROMs); 12. Interpolation for parametric ROMs.