Bays' Problem Solving Approach to Machine Learning

Bays worked out a way that described the sort of probability relationship between different discrete events. And using his reasoning, you can work forward or backward based on probabilities. It's an important example of conditional probability. A lot of what machine learning is really boiled down to is dealing with different probabilities, not certainties.