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Lecture
Neural Networks: Random Features and Kernel Regression
Description
This lecture covers the use of random features in neural networks, kernel regression, and the application of stochastic gradient descent. It explains the equivalence between neural networks and kernel regression, emphasizing the role of activation functions and hidden layers.
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