learningIn supervised learning an algorithm learns the input-to-output relationship after being provided both the inputs and the respective outputs. For example, the input might be a set of photos and the output might be a set of corresponding labels. In unsupervised learning the algorithm does not have access to the output, so the goal is to infer the underlying structure of the 