Markov Models

Markov Models are statistical models that are used to represent systems that change over time. They are based on the Markov property, which states that the future state of a system depends only on its current state and not on any previous states. In Data Science and Artificial Intelligence, Markov Models are used to model a wide range of systems, including natural language processing, speech recognition, image processing, and financial modeling. They are particularly useful in situations where the system being modeled has a large number of possible states and transitions between those states are probabilistic. Markov Models can be used to predict the future state of a system, given its current state, and can also be used to generate new sequences of states that are similar to those observed in the training data.
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