Write a function that can shift an MNIST image in any direction $($left$,$ right, up$,$

or down$)$ by one pixel$\mathrm{.}5$ Then, for each image in the training set, create four shifted copies $($one per direction$)$ and add them to the training set. Finally, train your

best model on this expanded training set and measure its accuracy on the test set.

You should observe that your model performs even better now! This technique of

artificially growing the training set is called data augmentation or training set

expansion.