[02/06/2013] Course Project Stage 2: Proposal is out in blackboard, due on 2/12.
[01/25/2013] Homework is out in blackboard and due on Feb. 4.
[01/21/2013] Course Project Stage 1: Group Sign-up due in Blackboard
[01/21/2013] No class: MLK Day. Makeup class will be on January 25- Snell Library Room 295 from 6-9 pm
[01/07/2013] First day of classes
(Future lectures and events are tentative.)
| Week# | Date | Topic | Slides | Assignment | Project | Reading (Textbook or Other Materials) |
| 1 | Jan. 7 | Introduction and Know Your Data |
01Intro [pptx][pdf] 02Data [pptx][pdf] |
Read Chapter 1 (Introduction) and Chapter 2 (Know Your Data). | ||
| 2 | Jan. 14 |
Course Project Introduction Data Preprocessing |
Course project overview [pdf] 03Preprocessing[pptx][pdf] |
Read Chapter 3 (Data Preprocessing). | ||
| 3 | Jan. 21 | No class: MLK Day | Team formation due | |||
| 3 | Jan. 25 |
Makeup class for Jan. 21:
Time: 6-9pm, Location: Snell Library 295
(Note classroom changes!) Mining Frequent Patterns and Associations: Basic Concepts |
06FPBasic[pptx][pdf] | Assign#1 out | Read Chapter 6. | |
| 4 | Jan. 28 | Mining Frequent Patterns and Associations: Advanced Methods | 07FPAdvanced[pptx][pdf] | Read Chapter 7. | ||
| 5 | Feb. 4 | Classification Part 1: overview, decision tree, rule-based classification, and model evaluation | Classification_1[pptx][pdf] | Assign#1 due | Read 8.1, 8.2, 8.4, 8.5 | |
| 6 | Feb. 11 | Classification Part 2: ANN, SVM | Classification_2[pptx][pdf] | Assign#2 out |
Proposal due on 2/12 | Read 9.2, 9.3 ANN by Tom Mitchell: http://www.cs.cmu.edu/afs/cs.cmu.edu/project/theo-20/www/mlbook/ch4.pdf SVM by Andrew Ng: http://cs229.stanford.edu/notes/cs229-notes3.pdf |
| 7 | Feb. 18 | No class: Presidents' Day | ||||
| 7 | Feb. 22 | Makeup class for Feb. 18: Canceled | Assign#2 due | |||
| 8 | Feb. 25 | Midterm Exam | ||||
| 9 | Mar. 4 | No class: Spring Break | ||||
| 10 | Mar. 11 | Classification Part 3: Naive Bayes, Bayesian Belief Networks, K-Nearest-Neighbor Classifiers | Classification_3[pptx][pdf] | Read 8.3, 9.1, 9.5 | ||
| 11 | Mar. 18 | Classification Part 4: frequent pattern-based classification, ensemble methods, and other topics | Classification_4 [pptx][pdf] | Midterm check point: 3/19 | Read 9.4, 8.6, 9.7 | |
| 12 | Mar. 25 | Cluster Analysis: Basic Concepts: partitioning methods, hierarchical methods | 10ClusteringBasic[pptx][pdf] | Assign#3 out | Read 10.1, 10.2, 10.3 | |
| 13 | Apr. 1 | Cluster Analysis: Basic Concepts: Density-based methods, grid-based methods | 10ClusteringBasic[pptx][pdf] | Read 10.4, 10.5, 10.6 | ||
| 14 | Apr. 8 | Cluster Analysis: Advanced Methods: revisit k-means, mixture models, EM-algorithm, kernel k-means, SCAN, spectral clustering | 11ClusteringAdvanced [pptx][pdf] | Assign#3 due (Apr. 9) | Read 11.1, 11.3 | |
| 15 | Apr. 15 | No class: Patriots' Day | Final report, data, and code due: 4/16 | |||
| 16 | Apr. 22 | Final Exam |