CS 10701 Lecture 29

Twelfth Lecture on Introduction to Machine Learning

Instance Based Learning Part Two

Testing Hypotheses

General Homework

Neural Networks and HMM

Bayesian Networks and Graphical Models

Grasp Classification Feature Selection

Expectation Maximization Overview

Baum-Welch Algorithm for HMMs Part Three

Baum-Welch Algorithm for HMMs Part Two

Theory of Computational Learning

Inference in Bayesian Networks - Introduction to Machine Learning

Revisiting Learning via Bayes Optimal Classifier Naive Bayes