EderSantana/awesomeMLmath

Information Theory Here is the deal, a probability density function (pdf) is as much as we can know about a radom variable. Machine Learning is about estimating "momements" (you should learn that) of a pdf. If your random variable is not Gaussian, you will need more than mean and variance to correctly describe it (mean and var are the 1st and 2nd order moments).