Introduction to Markov chain: simplified
Markov chain is a simple concept which can explain most complicated real time processes.Speech recognition, Text identifiers, Path recognition and many other Artificial intelligence tools use this simple principle called Markov chain in some form. In this article we will illustrate how easy it is to understand this concept.Introduction to Markov chain simplified
Markov chain is based on a principle of “memorylessness”. In other words the next state of the process only depends on the previous state and not the sequence of states. This simple assumption makes the calculation of conditional probability easy and enables this algorithm to be applied in number of scenarios. In this article we will restrict ourself to simple Markov chain. In real life problems we generally use Latent Markov model, which is a much evolved version of Markov chain. We will also talk about a simple application of Markov chain in the next article.