In this third part of the series, we start to see our unknown variables such as weights as Random Variables as well. I explain and show how to use Bayes' rule to get the distribution overweights and how to find the most probable value using MAP (Maximum a Posteriori)
This tutorial is based on the content from chapter 1 of Dr. Bishop's book.