Deep Learning -- not only for the big ones

It may sound a bit obvious, but sometimes we miss the power of this kind of solution to solve small data problems -- I'm talking about Data Augmentation. The idea behind Data Augmentation is -- Points nearby a certain point (in hyperspace) represent a similar behavior. For eg: An image of a dog with increased contrast or brightness is still an image of a dog. Let's talk about SMOTE in more detail. To simplify we can define the concept behind SMOTE as "Birds of the same feather flock together", which reduced in data terms means that data-points that are close to each other in the hyperspace represent similar behavior so they can be approximated as new data-points for the dataset.