LGM
Learning Graphical Models Repository.
In this work the scope was to implement a Hidden Markov Model module using the object oriented programming language Python in the version 2.7. The implementation exposes methods for generating sequences, finding the most probable sequence of hidden states (Viterbi algorithm) and estimating the parameters of a HMM from observations (Baum - Welch algorithm)