Tutorial 4: Introduction to Bayesian Decision Theory & Cost functions

This tutorial focuses on Bayesian Decision Theory, which combines the posterior with cost functions that allow us to quantify the potential impact of making a decision or choosing an action based on that posterior. Cost functions are therefore critical for turning probabilities into actions!

Overview of this tutorial:

1. Implement three commonly-used cost functions: mean-squared error, absolute error, and zero-one loss
2. Discover the concept of expected loss
3. Choose optimal locations on the posterior that minimize these cost functions