SSL is a problem setup in ML, Where we look to answer the question " Can we design the task in such a way that we can generate virtually unlimited labels from existing images and use that to learn the representations, Here, we replace the human annotation block by creatively exploiting some property of data to set up a pseudo-supervised task. Once we learn representations from these images, we can use transfer learning to fine-tune it on some supervised task like image classification of a few examples