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Hidden Markov Models (HMMs) are a class of probabilistic graphical model that allow us to predict a sequence of unknown (hidden) variables from a set of observed variables. A simple example of an HMM is predicting the weather (hidden variable) based on the type of clothes that someone wears (observed).
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