Entropy in machine learning
A brief overview of entropy, cross-entropy, and their usefulness in machine learning
Entropy is a familiar concept in physics, where it is used to measure the amount of “disorder” in a system. In 1948, mathematician Claude Shannon expanded this concept to information theory in a paper titled, “A Mathematical Theory of Communication”. In this article, I’ll give a brief explanation of what entropy is, and why it is relevant to machine learning.