Linear Regression, Gradient Descent, Machine Learning, Deep Learning, Naem Azam.
corresponding loss is computed. The parameters are updated after every training sample. Algorithm for stochastic gradient descent As mentioned, this algorithm takes one example per iteration. Let (x(I), y(I) be the training sample Stochastic Gradient Descent Advantages It is computationally fast as