Supervised V Unsupervised Machine Learning -- What's The Difference?

In recent articles I have looked at some of the terminology being used to describe high-level Artificial Intelligence concepts – specifically machine learning and deep learning. In this piece, I want to look at two other concepts which are vital to understanding how machines are becoming increasingly smarter and able to perform tasks which previously could only be done by humans. Supervised and unsupervised learning describe two ways in which machines - algorithms - can be set loose on a data set and expected to learn something useful from it. Today, supervised machine learning is by far the more common across a wide range of industry use cases. The fundamental difference is that with supervised learning, the output of your algorithm is already known – just like when a student is learning from an instructor.