Stochastic Gradient Descent : Stochastic gradient descent is used to calculate the gradient and update the parameters by using only a single training example.
Batch Gradient Descent : Batch gradient descent is used to calculate the gradients for the whole dataset and perform just one update at each iteration.
Mini-batch Gradient Descent : Mini-batch gradient descent is a variation of stochastic gradient descent. Instead of a single training example, mini-batch of samples is used. Mini-batch gradient descent is one of the most popular optimization algorithms.