In data engineering, augmentation is a process by which we create various transformations of the available data in the ML training dataset. Augmentation task examples are the perturbation of an image in different ways. Augmentation aims at increasing the amount of data input provided to a model to better fit the data into the model and make the ML model generalize well.
