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directly observe the weather states from the data. # Example of a Markov Chain States = [‘Rain’, ‘Dry’] Transition_probabilities = { ‘Rain’: {‘Rain’: 0.7, ‘Dry’: 0.3}, ‘Dry’: {‘Rain’: 0.2, ‘Dry’: 0.8} } Initial_probabilities = {‘Rain’: 0.4, ‘Dry’: 0.6} In contrast, an HMM has additional states that