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Explore a detailed code walkthrough demonstrating the implementation of Physics-Informed Neural Networks (PINNs) for solving the Burgers equation. Gain insights into the practical application of PINNs in computational fluid dynamics and learn how to leverage machine learning techniques to solve complex partial differential equations. Follow along as the instructor breaks down the code structure, explains key components, and highlights important considerations for successfully applying PINNs to the Burgers equation.
