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| Instructor:
Pedro Domingos Office: Sieg 216 Office hours: Wednesdays 5:30-6:20, and by appointment |
TA: David
Grimes Office: Sieg 226a Office hours: Wednesdays 5:30-6:20, and by appointment |
Class meets:
Wednesdays 6:30-9:20 in EE1-003
| Week | Topic |
|---|---|
| Week 1 (Mar 28) | Introduction; data warehousing and OLAP |
| Week 2 (Apr 4) | Decision trees |
| Week 3 (Apr 11) | Rule induction |
| Week 4 (Apr 18) | Bayesian learning |
| Week 5 (Apr 25) | Neural networks |
| Week 6 (May 2) | Genetic algorithms, model ensembles |
| Week 7 (May 9) | Instance-based learning |
| Week 8 (May 16) | Learning theory |
| Week 9 (May 23) | Association rules |
| Week 10 (May 30) | Clustering |
| Schedule | Assignment | % of Grade | Topic | Additional Info |
|---|---|---|---|---|
| Weeks 2-3 | Homework 1 | 12.5 | Warehousing and OLAP, decision trees | |
| Weeks 3-6 | Project 1 | 37.5 | Clickstream mining | |
| Weeks 6-7 | Homework 2 | 12.5 | Rule ind., Bayesian learning, neural nets, GAs | |
| Weeks 7-9 | Project 2 | 25 | Collaborative filtering | |
| Weeks 9-10 | Homework 3 | 12.5 | Ensembles, IBL, theory, assoc. rules |
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Department of Computer Science & Engineering University of Washington Box 352350 Seattle, WA 98195-2350 (206) 543-1695 voice, (206) 543-2969 FAX [comments to grimes@cs.washington.edu] |
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