Data Driven Science and Engineering

This book PDF is perfect for those who love Computers genre, written by Steven L. Brunton and published by Cambridge University Press which was released on 05 May 2022 with total hardcover pages 615. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Data Driven Science and Engineering books below.

Data Driven Science and Engineering
Author : Steven L. Brunton
File Size : 55,5 Mb
Publisher : Cambridge University Press
Language : English
Release Date : 05 May 2022
ISBN : 9781009098489
Pages : 615 pages
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Data Driven Science and Engineering by Steven L. Brunton Book PDF Summary

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Data Driven Science and Engineering

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

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Data Driven Science and Engineering

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

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Data Driven Science and Engineering

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Data Driven Modeling   Scientific Computation

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Machine Learning Control     Taming Nonlinear Dynamics and Turbulence

This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated and detailed in Chapters 1 and 2. In Chapter 3, methods of

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Informatics for Materials Science and Engineering

Materials informatics: a ‘hot topic’ area in materials science, aims to combine traditionally bio-led informatics with computational methodologies, supporting more efficient research by identifying strategies for time- and cost-effective analysis. The discovery and maturation of new materials has been outpaced by the thicket of data created by new combinatorial and

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Data-driven dynamical systems is a burgeoning field?it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific

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