Machine Learning, Data Science, Loss Function, Regression, Classification.
approach of using KL-Divergence as a loss function without getting into its math. We want to approximate the true probability distribution P of our target variables with respect to the input features, given some approximate distribution Q. Since KL-Divergence is not symmetric, we can do this in two