Data augmentation is a family of techniques that are used to increase the amount of training data. Traditionally, these techniques are used for tasks that have limited training data, such as in medical imaging. However, in the last few years, they have shown to be useful even when we have a lot of data—augmented data can make our models more robust to noise and even adversarial attacks.
