Describe, compare, and contrast the three main approaches to probability

Understand the fundamentals of the Bayesian approach—such as conditional probability, priors, and updating beliefs

Apply Bayesian methods such as Bayes theorem and contingency tables to simple problems

Describe two Bayesian machine learning methods—multinomial and gaussian Bayes classifiers

Recognize the benefits of using these machine learning methods for modeling complex scenarios

Evaluate the results of the machine learning tests against business goals in Python