Markov chain applications

Now, let's look at a series of practical applications that can be made using Markov chains. We will introduce the problem and then analyze the Python code that will allow us to simulate how it works.

Introducing random walks

Random walks identify a class of mathematical models used to simulate a path consisting of a series of random steps. The complexity of the model depends on the system features we want to simulate, which are represented by the number of degrees of freedom and the direction. The authorship of the term is attributed to Karl Pearson who, in 1905, first referred to the term casual walk. In this model, each step has a random direction that evolves through a random process involving known quantities that follow a precise statistical distribution. The path that's traced over time will not necessarily be descriptive of real motion: it will simply return the evolution of a variable over time. This is the reason for the widespread...