A Gentle Introduction to the Central Limit Theorem for Machine Learning

The central limit theorem is an often quoted, but misunderstood pillar from statistics and machine learning. It is often confused with the law of large numbers. Although the theorem may seem esoteric to beginners, it has important implications about how and why we can make inferences about the skill of machine learning models, such as whether one model is statistically better than another and confidence intervals on models skill. In this tutorial, you will discover the central limit theorem and the implications of this important pillar of statistics and probability on applied machine learning. A Gentle Introduction to the Central Limit Theorem for Machine Learning Photo by Alan Levine, some rights reserved.