Bayesian Learning Lecture

Abstract

This lecture overviews Bayesian Learning that has many applications in pattern recognition and clustering. It covers the following topics in detail: Bayes probability theorem. Bayes decision rule. Bayesian classification. Maximum A-Posteriori Criterion. Maximum Likelihood Criterion. Normally Distributed Sample Classification. Bayesian clustering.

Linear decision boundary for two 2D Gaussian pdfs having equal C.

Bayesian-Learning-v3.3.1

Understanding Questionnaire

https://docs.google.com/forms/bayesian-learning

Tutorial Exercises

1. Bayesian Learning Tutorial Exercises
   1. Bayesian Classification of Normal Data Tutorial Exercise
   2. Bayesian Classification of Three-class 1D Data Tutorial Exercise
   3. Bayesian Classification of Two-class 1D Data Tutorial Exercise
   4. Bayesian Signal Classification Tutorial Exercise