Bayesian probability can be challenging, especially when you see the formula used to calculate the probabilities. However, there is a way to approach the technique in a more inviting way. Michael Larionov will guide us through Bayes-land.
If you flip a coin and it shows heads, what is the probability that it will show heads the second time? This and other simple problems can be solved using Bayesian probability.
Being the foundation of many machine learning algorithms, Bayesian theory, however, feels intimidating to many who attempt to understand it.
In this meetup we will discuss the Bayesian probability in a non-intimidating way. Join us to get a taste of Bayes that hopefully encourages you to continue.
Michael Larionov, Data Architect and Data Scientist, currently working at Resideo Technologies. Ph.D. in Physics and Mathematics with more than 22 years of experience as a programmer, dev. architect and data scientist.
I am interested in machine learning algorithms from Bayesian perspective.