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Cambridge University Press Cambridge Data-Driven Fluid Mechanics Machine Learning Book

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Description

Expand your expertise in fluid dynamics with this essential text from Cambridge University Press. As data-driven methods become a core part of the modern methodological portfolio, this book helps students and practitioners bridge the gap between traditional physics and new computational disciplines. It covers vital areas including computer science, statistics, optimization, signal processing, and nonlinear dynamics. Fluid mechanics serves as a fertile ground for applying machine learning and pattern recognition. This resource demonstrates how to use data-driven methods while maintaining the necessary constraints and interpretations provided by basic physics. It is designed for those looking to integrate diverse fields like control and statistical analysis into their fluid dynamics research and practice.

Key Features

This Cambridge University Press book covers the integration of machine learning with first principles in fluid mechanics.

The text explores essential disciplines including computer science, statistics, optimization, and signal processing.

Learn to apply pattern recognition and nonlinear dynamics to fluid mechanics research and data analysis.

Gain knowledge on using data-driven methods while applying constraints based on basic physics.

This English language book provides practical knowledge for students and practitioners in the field of fluid dynamics.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
02 February 2023
Listed Since
24 March 2022

Barcode

No barcode data available

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