What is Bayes Theorem?

If you've been learning about data science or machine learning, there's a good chance you've heard the term "Bayes Theorem" before, or a "Bayes classifier". These concepts can be somewhat confusing, especially if you aren't used to thinking of probability from a traditional, frequentist statistics perspective. This article will attempt to explain the principles behind Bayes Theorem and how it's used in machine learning. Bayes Theorem is a method of calculating conditional probability. The traditional method of calculating conditional probability (the probability that one event occurs given the occurrence of a different event) is to use the conditional probability formula, calculating the joint probability of event one and event two occurring at the same time, and then dividing it by the probability of event two occurring.