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Interactive Learning
Model sequences with hidden states. Hidden Markov Models is a advanced machine learning algorithm used for modeling uncertainty. Before learning Hidden Markov Models, you should understand: conditional-probability, bayes-theorem. Real-world applications include: Speech recognition, Gene finding, Weather prediction. This is an advanced topic requiring solid prerequisites.
Speech recognition
Gene finding
Weather prediction
Interactive lesson with visualizations and practice problems
Part of the Hidden Markov Models lesson in Machine Learning