Home
MIT 6.790
Machine Learning
Lecture 1: Introduction to Machine Learning
§
Setting Up
§
The Optimal Hypothesis (Given the Distribution!)
Lecture 2: ERM and MLE
§
Empirical Risk Minimization
§
Overfitting
§
Maximum Likelihood Estimation
§
MLE Advantages and Disadvantages
Lecture 3: Bayesian Learning
Lecture 4: Linear Regression
Lecture 5: Bayesian Linear Regression
§
Problems with Linear Regression
§
Bayesian Linear Regression: Theory
§
Bayesian Linear Regression: Performance