From Entropy to KL Divergence: A Comprehensive Guide

KL Divergence is a fundamental concept in information theory and statistics. We explore entropy as the foundation, then delve into KL Divergence, its mathematical formulation, Monte Carlo Estimators, and applications in classification, generative modeling, knowledge distillation, reinforcement learning, and LLMs.