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Neural networks under SGDExplores the optimization of neural networks using Stochastic Gradient Descent (SGD) and the concept of dual risk versus empirical risk.
Gradient, divergenceCovers the definitions of gradient and divergence, including the Cartesian coordinate system and the divergence theorem.
Vector Calculus TheoremsExplores the Gauss and Green theorems in vector calculus, showcasing their applications through practical examples and geometric interpretations.
Symmetries and Conservation LawsCovers symmetries and conservation laws in fluid dynamics, emphasizing the importance of maximizing symmetries in ideal fluid systems.