Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
- Downloads：9726
- Type：Epub+TxT+PDF+Mobi
- Create Date：2022-08-17 16:21:35
- Update Date：2025-09-07
- Status：finish
- Author：Steven L. Brunton
- ISBN：1009098489
- Environment：PC/Android/iPhone/iPad/Kindle
Reviews
Claudio Noguera
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Too technical for my liking， I'd like to have a longer book that is easier to read。It is a reference book， not a book to learn while you read it。However， the accompanying lectures available in YouTube and the book website with actual code are very useful Too technical for my liking， I'd like to have a longer book that is easier to read。It is a reference book， not a book to learn while you read it。However， the accompanying lectures available in YouTube and the book website with actual code are very useful 。。。more
Marv
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This work is a excellent book that adequately explains， what I believe， to be the future direction of technology。 It explains the combining of machine learning with data mining to control complex physics and engineering problems with the use of algorithms discussed， by Brunton and Kutz。 A fantastic engineering read。
JC Perrin
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This book is INSANELY cool。 Brunton and Kutz build their way up from fundamental techniques of linear algebra， through almost every major aspect of classical control， to some of the cutting edge techniques of modern control （like SINDy which they've helped develop）。 And yet， though it touches on so many complex ideas， they manage to write in simple， understandable english。 They center almost every new idea in examples or illustrations help illustrate the real-world meaning。 And their explanation This book is INSANELY cool。 Brunton and Kutz build their way up from fundamental techniques of linear algebra， through almost every major aspect of classical control， to some of the cutting edge techniques of modern control （like SINDy which they've helped develop）。 And yet， though it touches on so many complex ideas， they manage to write in simple， understandable english。 They center almost every new idea in examples or illustrations help illustrate the real-world meaning。 And their explanations are written with such lucidity that concepts I had to prove to myself in grad school （like projecting functions into different bases） seem almost self-evident。 I've used several system identification techniques they present （like Dynamic Mode Decomposition） to solve problems at work， and I see several more opportunities for direct applications of the stuff they discuss here。 For a taste of what's inside check out the book website -- databookuw dot com -- or Brunton's youtube channel。 Also check out Brunton's lab website -- eigensteve dot com -- although the papers there are dense and are targeted at researchers。 。。。more
Oleksandr Nikitin
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