Geometric Introduction to Markov Chain Monte Carlo
MCMC is a foundational concept of machine learning. Animations in Excel provide simple conceptual understanding.
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191
students
2 hours
content
Apr 2024
last update
$54.99
regular price
What you will learn
Understand what is meant by Markov Chain Monte Carlo (MCMC).
Apply and understand random walk methods.
Solve provided problems using MCMC.
Understand the two main algorithms (Gibbs Sampling and Metropolis-Hastings algorithm) and the applicability of them.
Understand what is meant by conditional probability, transitional probability and non-conditional probability.
Understand that although MCMC is directly relevant to conditional problems, it can also be applied to non-conditional problems.
For VBA developers understand how to create animations useful for explaining mathematical concepts.
Learn how to apply the Metro-Hastings algorithm to problems – and to expose the VBA code that focuses on the application of Metropolis-Hastings algorithm.
Although the code is written in VBA it would be obvious to a developer how the methodology is applicable to other software languages.
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udemy ID
4/2/2024
course created date
4/7/2024
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