Stochastic Gradient Descent : In SGD, we use only a single training example for calculation of gradient and parameters.
Batch Gradient Descent : In BGD, we calculate the gradient for the whole dataset and perform the updation at each iteration.
Mini-batch Gradient Descent : Mini-batch Gradient Descent is a variant of Stochastic Gradient Descent. In this gradient descent, we used mini-batch of samples instead of a single training example.
