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    Data-Driven Science and Engineering

    Steve Brunton5.0
    20 hours
    English
    0/98 уроков (0%)
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    Data-Driven Science and Engineering

    YouTube·Data Science

    Explore a comprehensive 20-hour video series on data-driven science and engineering, covering machine learning, dynamical systems, and control. Dive into topics like Singular Value Decomposition, Principal Component Analysis, Fourier Analysis, and Reinforcement Learning. Learn to apply these concepts using both MATLAB and Python through practical examples in image compression, eigenfaces, data denoising, and PDE solving. Gain insights into advanced topics such as randomized SVD, wavelets, Laplace transforms, and deep reinforcement learning for fluid dynamics and control. Enhance your understanding of data-driven modeling, machine learning in fluid mechanics, and nonlinear control techniques like Hamilton-Jacobi-Bellman equations and dynamic programming.

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