Deep Learning, Regularisation, Optimization Algorithms, Deep Neural Networks, Gradient Descent.
what will happen if we have a large training set, say m = 5,000,000? If we process through all of these training examples in every training iteration, the gradient descent update will take a lot of time. Instead, we can use a mini batch of the training examples and update the weights based on them.