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Results tagged with gradient-descent
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user 136310
Gradient Descent is an algorithm for finding the minimum of a function. It iteratively calculates partial derivatives (gradients) of the function and descends in steps proportional to those partial derivatives. One major application of Gradient Descent is fitting a parameterized model to a set of data: the function to be minimized is an error function for the model.
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Understanding Learning Rate in depth
It depends on the loss function, The loss function of data set 1 might have a different shape than the loss function of a different dataset, for example, they might one might be a simple convex functi …
