Epoch
One full pass of the training algorithm over the entire training dataset.
Training normally takes many epochs, since one look at the data is rarely enough. Too few and the model underfits; too many and it starts memorising. Very large models sometimes train for less than a single epoch simply because the dataset is enormous.
In practice: Ten epochs over 50,000 images means the model saw each image ten times.