Introduction to (Statistical)
Machine Learning
Brown University CSCI1420 & ENGN2520
Prof. Erik Sudderth
Lecture for Sept. 12, 2013:
Generative Models for Classification
Model Validation, Decision Theo
Introduction to (Statistical)
Machine Learning
Brown University CSCI1420 & ENGN2520
Prof. Erik Sudderth
Lecture for Sept. 17, 2013:
Decision Theory and ROC Curves,
Continuous Random Variables, Frequen
Introduction to (Statistical)
Machine Learning
Brown University CSCI1420 & ENGN2520
Prof. Erik Sudderth
Lecture for Sept. 10, 2013:
Probability: Discrete Random Variables
Classification: Overfitting &
Introduction to (Statistical)
Machine Learning
Brown University CSCI1420 & ENGN2520
Prof. Erik Sudderth
Lecture for Sept. 24, 2013:
Decision Theory for Continuous Variables,
Bayesian Learning and Mode
Introduction to (Statistical)
Machine Learning
Brown University CSCI1420 & ENGN2520
Prof. Erik Sudderth
Lecture for Sept. 26, 2013:
Bayesian Model Selection, Monte Carlo Methods,
Multivariate Gaussian
Introduction to (Statistical)
Machine Learning
Brown University CSCI1420 & ENGN2520
Prof. Erik Sudderth
Lecture for Oct. 3, 2013:
Linear Regression & Least Squares,
Bayesian Linear Regression
Many fig
Introduction to (Statistical)
Machine Learning
Brown University CSCI1420 & ENGN2520
Prof. Erik Sudderth
Lecture for Sept. 19, 2013:
Maximum Likelihood Parameter Estimation,
Bayesian Estimation of Prob
Introduction to (Statistical)
Machine Learning
Brown University CSCI1420 & ENGN2520
Prof. Erik Sudderth
Lecture for Oct. 8, 2013:
Bayesian Regression & Predictive Distributions,
Probit Regression & Lo
Introduction to (Statistical)
Machine Learning
Brown University CSCI1420 & ENGN2520
Prof. Erik Sudderth
Lecture for Oct. 1, 2013:
Gaussian Classification & Discriminant Analysis,
Linear Regression & L