| Date |
Topics |
Slides |
Reading |
| 1/4/12 |
Introduction |
(pdf)
|
None for today |
| 1/6/12 |
Learning decision trees: overview & information gain heuristic |
(pdf)
|
Decision Trees |
| 1/09/12 |
Learning Decision Trees: Overfitting & Pruning |
(pdf)
|
|
| 1/13/12 |
Learning Decision Trees: Handling Continuous & Missing Values |
(pdf)
|
|
| 1/23/12 |
Probability Theory & Point Estimation |
(pdf)
|
Bishop 1.1, 2.1
|
| 1/25/12 |
Point Estimation |
(pdf)
|
Bishop 2.1
|
| 1/27/12 |
Naive Bayes |
(pdf)
|
Naive Bayes (Stanford)
Naive Bayes (Mitchell), Bishop 1.5.4
|
| 1/30/12 |
Gaussian Naive Bayes |
(pdf)
|
|
| 2/1/12 |
Logistic Regression 1 |
(pdf)
|
(Mitchell)
|
| 2/3/12 |
Logistic Regression 2 |
(pdf)
|
|
| 2/6/12 |
Logistic Regression Finale + Perceptron |
(pdf)
|
Bishop 4.1.1, 4.1.2, 4.1.7
|
| 2/8/12 |
Ensembles + Bias/Variance Tradeoff |
(pdf)
|
Ensemble Learning by T.
Dietterich, Bishop 14.2, 14.3
|
| 2/10/12 |
Boosting |
(pdf)
|
|
| 2/13/12 |
Review / Neural Networks |
(pdf)
|
|
| 2/15/12 |
Midterm |
|
|
| 2/17/12 |
Decide.com (Oren Etzioni) |
|
|
| 2/20/12 |
Holiday |
|
|
| 2/22/12 |
Farecast / Data Labeling (Oren Etzioni) |
| KDD paper on Farecast
|
| 2/24/12 |
Clustering (K-means and Hierarchical Agglomerative Clustering) |
(pdf)
|
Bishop 9.1 and Manning IR book HAC
|
| 2/27/12 |
Expectation Maximization |
(pdf)
|
Bishop 9.2 (Optional: 9.3 and 9.4)
|
| 2/29/12 |
Principle Component Analysis |
(pdf)
|
Bishop 12.1
|
| 3/2/12 |
Markov Decision Processes (MDPs), Mausam |
(pdf)
|
|
| 3/5/12 |
Reinforcement Learning |
(pdf)
|
Kevin Murphy's introduction, but ignore the POMDP part.
|
| 3/7/12 |
Instance-Based Learning |
(pdf)
|
Bishop 1.4, 2.5
|
| 3/9/12 |
Summary, SVMs, Co-training |
(pdf)
|
|
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