This is part one in a series of topics I consider fundamental to machine learning. Probability theory is a mathematical framework for quantifying our uncertainty about the world. It allows us (and our software) to reason effectively in situations where being certain is impossible. Probability theory is at the foundation of many machine learning algorithms. The goal of this post is to cover the vocabulary and mathematics needed before applying probability theory to machine learning applications.
Feb-3-2019, 07:37:50 GMT