Week | Tuesday | Thursday | Readings |
---|---|---|---|
January 13 | What is Machine Learning? | Chapter 1 | |
January 18, 20 | Examples of Machine Learning Applications | Apriori association rule algorithm | Chapters 1, 2, 3.9 |
January 25, 27 | PAC learning for finite hypothesis spaces VC dimension examples | HW1 due. Quiz 1 | Chapter 2 |
February 1, 3 | Candidate Elimination algorithm | Naive Bayes classifier | Chapter 2, 3 |
February 8, 10 | HW2 due. Laplace estimator, 1R classifier, LMS | no class | Chapter 3, 9 |
February 15, 17 | Quiz 2. (Decision trees) | Information theory and entropy (odd ball example), Probability densities | Chapter 9, Appendix |
February 22, 24 | k-nearest neighbor | kd-trees | Chapter 8, 4 |
March 1, 3 | Linear discrimination | Support Vector Machines | Chapter 10 |
March 8, 10 | A practical guide to SVM classification | SVM: Kernel functions, examples | "A practical guide to Support Vector Classification" by Hsu, Chang, Lin |
March 15, 17 | Perceptron | Dr. Freeman "Perceptron is a process of creating self-renewal", at 6pm in PSL | Chapter 11 |
March 22, 24 | Spring Break | ||
March 29, 31 | Neural networks: Gradient descent and the delta rule | Neural networks: Backpropagation algorithm | Chapter 11 |
Week | Tuesday | Wednesday | Thursday |
April 5, 7 | Evan "Clustering and You" | Mayur "Decision Tree Methods" | |
April 12, 13, 14 | Brian | Adam | Kalyan |
April 19, 20, 21 | Senlin | Brad | Mike |
April 26, 28 | no classes | ||
May 3, 5 | Vitus | Jacob |