MARC状态：已编 文献类型：西文图书 浏览次数：67
- 题名/责任者:
- Data-driven science and engineering : machine learning, dynamical systems, and control / Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington.
- 出版发行项:
- Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2019.
- 出版发行项:
- ? 2019
- ISBN:
- 9781108422093
- ISBN:
- 1108422098
- 载体形态项:
- xxii, 472 pages : some color illustrations ; 27 cm
- 个人责任者:
- Brunton, Steven L. (Steven Lee), 1984- author.
- 附加个人名称:
- Kutz, Jose Nathan, author.
- 论题主题:
- Engineering-Data processing.
- 论题主题:
- Science-Data processing.
- 论题主题:
- Mathematical analysis.
- 论题主题:
- Engineering-Data processing.
- 论题主题:
- Mathematical analysis.
- 论题主题:
- Science-Data processing.
- 论题主题:
- Engineering-Data processing.
- 论题主题:
- Science-Data processing.
- 论题主题:
- Mathematical analysis.
- 中图法分类号:
- TP301.6
- 书目附注:
- Includes bibliographical references and index.
- 摘要附注:
- "Data-driven discovery is revolutionizing the modelling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modelling 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"--
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| 索书号 | 条码号 | 年卷期 | 馆藏地 | 书刊状态 | 还书位置 |
| TP301.6/B911 | 350000529 |  外文书库
|
可借 | 外文书库 |
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