Markov chains are used to predict future outcomes of different processes using present state information.

A Markov chain is **a stochastic model** that describes a
sequence of possible events. In this sequence, the probability of every event
depends on the state of the previous event.

Markov chains are used in different aspects of real life. The following are some examples of Markov chains:

- The stock exchange. Stock market trends are not dependent on past events. Only the current state of the stocks can determine the future state of stocks.
- Predicting traffic flows. If we have been given recent or current values of traffic flow, we can predict how the traffic flow will be in the future.
- Page rank determination by Google.
- Predicting the weather using probabilities.
- Determining the possibilities of consumers switching from one brand to another.

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