The Simpler Brother of OLS Regression for Machine Learning

Nonparametric's took me a while to get my head around. On the one hand, all I had ever studied involved making the formulae of a predictive model differentiable and optimizing in regards to the individual or set of parameters (think linear regression or GMM). On the other hand, the majority of the nonparametric methods were being used in classification (Random Forests, KNN, etc). But some of the best methods are nonparametric. They do not assume a particular family of distributions and try to select the best-fit ones, they make judgments without assuming a distribution. Keep up to date with my latest articles here!