Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control | Agenda Bookshop Skip to content
Please note that books with a 10-20 working days delivery time may not arrive before Christmas.
Please note that books with a 10-20 working days delivery time may not arrive before Christmas.
A01=J. Nathan Kutz
A01=Steven L. Brunton
Age Group_Uncategorized
Age Group_Uncategorized
Author_J. Nathan Kutz
Author_Steven L. Brunton
automatic-update
Category1=Non-Fiction
Category=PBT
Category=PBU
Category=PBWH
Category=PHU
Category=TJFM
Category=UYA
Category=UYQM
Category=UYS
COP=United Kingdom
Delivery_Delivery within 10-20 working days
Language_English
PA=In stock
Price_€50 to €100
PS=Active
softlaunch

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

4.57 (42 ratings by Goodreads)

English

By (author): J. Nathan Kutz Steven L. Brunton

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. See more
Current price €59.84
Original price €62.99
Save 5%
A01=J. Nathan KutzA01=Steven L. BruntonAge Group_UncategorizedAuthor_J. Nathan KutzAuthor_Steven L. Bruntonautomatic-updateCategory1=Non-FictionCategory=PBTCategory=PBUCategory=PBWHCategory=PHUCategory=TJFMCategory=UYACategory=UYQMCategory=UYSCOP=United KingdomDelivery_Delivery within 10-20 working daysLanguage_EnglishPA=In stockPrice_€50 to €100PS=Activesoftlaunch
Delivery/Collection within 10-20 working days
Product Details
  • Weight: 1360g
  • Dimensions: 183 x 259mm
  • Publication Date: 05 May 2022
  • Publisher: Cambridge University Press
  • Publication City/Country: United Kingdom
  • Language: English
  • ISBN13: 9781009098489

About J. Nathan KutzSteven L. Brunton

Steven L. Brunton is the James B. Morrison Professor of Mechanical Engineering at the University of Washington and Associate Director of the NSF AI Institute in Dynamic Systems. He is also Adjunct Professor of Applied Mathematics and Computer Science and a Data-Science Fellow at the eScience Institute. His research merges data science and machine learning with dynamical systems and control with applications in fluid dynamics biolocomotion optics energy systems and manufacturing. He is an author of three textbooks and received the UW College of Engineering Teaching award the Army and Air Force Young Investigator Program (YIP) awards and the Presidential Early Career Award for Scientists and Engineers (PECASE) award. J. Nathan Kutz is the Robert Bolles and Yasuko Endo Professor of Applied Mathematics at the University of Washington and Director of the NSF AI Institute in Dynamic Systems. He is also Adjunct Professor of Electrical and Computer Engineering Mechanical Engineering and Physics and Senior Data-Science Fellow at the eScience Institute. His research interests lie at the intersection of dynamical systems and machine learning. He is an author of three textbooks and has received the Applied Mathematics Boeing Award of Excellence in Teaching and an NSF CAREER award.

Customer Reviews

No reviews yet
0%
(0)
0%
(0)
0%
(0)
0%
(0)
0%
(0)
We use cookies to ensure that we give you the best experience on our website. If you continue we'll assume that you are understand this. Learn more
Accept