Hidden Markov Models (HMM) were the mainstay of generative models a couple of years ago. Even though more sophisticated Deep Learning generative models have emerged, we cannot rule out the effectiveness of the humble HMM. After all, one of the most widely known principle (Occam’s Razor** states that if you have a number of competing hypothesis, the simplest one is the best one. The purpose of this blog post is to explore the mathematical basis on which HMMs are built.
