Unsupervised learning

Unsupervised learning is a method in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data.^[1] Within such an approach, a machine learning model tries to find any similarities, differences, patterns, and structure in data by itself. No prior human intervention is needed.^[1]

Other methods in the supervision spectrum are Reinforcement Learning where the machine is given only a numerical performance score as guidance,^[2] and Weak or Semi supervision where a small portion of the data is tagged, and Self Supervision.