Data augmentation is a technique where we apply transformations to an image and use both the original image and the transformed images to train on. Imagine we had a training set with a cat in it:
If we were to apply a horizontal flip to this image, we'd get something that looks like this:
This is exactly the same image, of course, but we can use both the original and transformation as training examples. This isn't quite as good as two separate cats in our training set; however, it does allow us to teach the computer ...
