Some interesting applications of Stochastic Processes using Jupyter Notebooks for descriptive and instructive illustrations are included in this repository and can be summarized in the following list:
- Markov Chains
- Random Walks
- Markov Chain Monte Carlo (MCMC) Sampling
- Monte Carlo Approximations
- Ergodic Theorem
- Ising Model
- Travelling Salesman Problem
Modelling a tennis match using Markov Chains.
Two dimensional Random Walk.
Approximating the value of 𝛑 using Monte Carlo Estimates.
Monte Carlo simulation of the two dimensional Ising Model.
Solving the Travelling Salesman Problem usng the Simulated Annealing Algorithm.
