Machine Learning

Bayesian Theorem and Concept Learning  Bayesian learning Topics Introduction Bayes theorem Concept learning Maximum Likelihood and least squared error hypotheses Maximum likelihood hypotheses for predicting probabilities Minimum description length principle, Bayes optimal classifier, Gibs algorithm, Naïve Bayes classifier, an example: learning to classify text,  Bayesian belief networks, the EM algorithm. What is Bayesian Learning? Bayesian learning is a type of machine learning that uses Bayesian probability theory to make predictions and decisions based on data.