What are Markov Chains? Explained With Python Code Examples

Markov chains are mathematical models used to predict future events based on current states, with applications in various fields such as finance, genetics, and robotics. This guide explains the key types of Markov chains, including Discrete-Time, Continuous-Time, and Hidden Markov Models, along with a Python code example demonstrating how to implement a Gaussian Hidden Markov Model. Markov chains are valued for their 'memoryless' property and their ability to model complex systems efficiently.