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Results tagged with gradient-descent
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user 22906
For questions surrounding gradient descent, a method for finding the optimum state of a parameterized function based on another function often called the loss or error function. It iteratively descends the loss surface to the minimum loss by adjusting parameters based on the product of the partial derivatives comprising the gradient and a learning rate.
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What is relation between gradient descent and regularization in deep learning?
Usually, when talking about regularization for neural networks there are 3 main types:
L1, L2 and dropout. All affect the gradient descent procedure.
L1 and L2 regularization is implemented in the lo …
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