Optimizer, Gradient Descent, Machine Learning, Adam, Sgd.
calculated as Error =(y actual — y pred)² It is very fast. It updates the weights after each error calculation. If there are 100 samples in the set, in an epoch, SGD updates the weights 100 times once after each sample is predicted by the model. Now, each time, it tries a new sample which in most