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Data-Driven Science and Engineering

- Machine Learning, Dynamical Systems, and Control
Af: Steven L. Brunton, J. Nathan Kutz Engelsk Hardback

Data-Driven Science and Engineering

- Machine Learning, Dynamical Systems, and Control
Af: Steven L. Brunton, J. Nathan Kutz Engelsk Hardback
Tjek vores konkurrenters priser
Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering a broad overview of the growing intersection of data-driven methods, machine learning, applied optimization, and classical fields of engineering mathematics and mathematical physics. With a focus on integrating dynamical systems modeling and control with modern methods in applied machine learning, this text includes methods that were chosen for their relevance, simplicity, and generality. Topics range from introductory to research-level material, making it accessible to advanced undergraduate and beginning graduate students from the engineering and physical sciences. The second edition features new chapters on reinforcement learning and physics-informed machine learning, significant new sections throughout, and chapter exercises. Online supplementary material – including lecture videos per section, homeworks, data, and code in MATLAB®, Python, Julia, and R – available on databookuw.com.
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kr 526
Fragt: 39 kr
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Tjek vores konkurrenters priser
Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering a broad overview of the growing intersection of data-driven methods, machine learning, applied optimization, and classical fields of engineering mathematics and mathematical physics. With a focus on integrating dynamical systems modeling and control with modern methods in applied machine learning, this text includes methods that were chosen for their relevance, simplicity, and generality. Topics range from introductory to research-level material, making it accessible to advanced undergraduate and beginning graduate students from the engineering and physical sciences. The second edition features new chapters on reinforcement learning and physics-informed machine learning, significant new sections throughout, and chapter exercises. Online supplementary material – including lecture videos per section, homeworks, data, and code in MATLAB®, Python, Julia, and R – available on databookuw.com.
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Produktdetaljer
Sprog: Engelsk
Sider: 614
ISBN-13: 9781009098489
Indbinding: Hardback
Udgave:
ISBN-10: 1009098489
Kategori: Matematisk modellering
Udg. Dato: 5 maj 2022
Længde: 33mm
Bredde: 261mm
Højde: 185mm
Forlag: Cambridge University Press
Oplagsdato: 5 maj 2022
Forfatter(e): Steven L. Brunton, J. Nathan Kutz
Forfatter(e) Steven L. Brunton, J. Nathan Kutz

Kategori Matematisk modellering

ISBN-13 9781009098489

Sprog Engelsk

Indbinding Hardback

Sider 614

Udgave

Længde 33mm

Bredde 261mm

Højde 185mm

Udg. Dato 5 maj 2022

Oplagsdato 5 maj 2022

Forlag Cambridge University Press