One iteration of mini$-$batch gradient descent $($computing on a single mini$-$batch$)$ is faster than one iteration of batch gradient descent.Training one epoch $($one pass through the training set$)$ using mini$-$batch gradient descent is faster than training one epoch using batch gradient descent.None of theseYou should implement mini$-$batch gradient descent without an explicit for$-$loop over different mini$-$batches, so that the algorithm processes all mini$-$batches at the same time $($vectorization$).$