This article will not be useful only for data scientists, programmers, mathematicians, statisticians, and other scientists, but also for everybody. This is part of the movement for Open data and Open information. We all want to learn topics based on our interests, that comes often through books. Unfortunately, most books are paid and are often […]
This notebook is a basic introduction into Stochastic Processes. It is meant for the general reader that is not very math savvy, like the course participants in the Math Concepts for Developers in SoftUni.
There is a basic definition. Some examples of the most popular types of processes like Random Walk, Brownian Motion or Weiner Process, Poisson Process and Markov chains have been given. Their basic characteristics and examples for some possible applications are stated. For all the examples there are simulations in Python, some are visualized.
The following packages have been used:
nympy
matplotlib.pyplot
random
scipy.stats
itertools
matplotlib.patches
