Consider two functions: f1(x, y) = (x − 2)^2 + (y − 3)^2 and f2(x, y) = (1 − (y − 3))^2 + 20((x + 3) − (y − 3)^2)^2 Starting with (x, y) = (0, 0) run the gradient descent algorithm for each function.

This notebook illustrates the nature of the Stochastic Gradient Descent (SGD) and walks through all the necessary steps to create SGD from scratch in Python. Gradient Descent is an essential part of ...

Master how mini-batches work, why they’re better than full batch or pure stochastic descent. #MiniBatchGD #SGD #DeepLearning ...

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