Date

Topic

Due

Aug 23 
Introduction, ML review 

Aug 25 
ML review, Orange 
Selection of presentation topic and date 
Aug 30 
Association rule mining, Sequence mining 

Sep 1 
Dimensionality reduction 

Sep 6 
Dimensionality reduction 
HW #1 due 
Sep 8 
Feature selection 

Sep 13 
Experiment Design and Analysis 

Sep 15 
Experiment Design and Analysis 
Critique due 
Sep 20 
Student presentation / discussion 
Critique due 
Sep 22 
Student presentation / discussion 

Sep 27 
Neural networks 

Sep 29 
Neural networks 

Oct 4 
Probabilistic graphs 
HW #2 due 
Oct 6 
Probabilistic graphs 
Critique due 
Oct 11 
Student presentation / discussion 
Critique due 
Oct 13 
Student presentation / discussion 
Critique due 
Oct 18 
Student presentation / discussion 

Oct 20 
Clustering and SOMs 

Oct 25 
Evolutionary algorithms 
Critique due 
Oct 27 
Student presentation / discussion 
Project proposal due, Critique due

Nov 1 
Student presentation / discussion 
Critique due 
Nov 3 
Student presentation / discussion 
Critique due 
Nov 8 
Student presentation / discussion 
HW #3 due 
Nov 10 
Trend analysis and forecasting 

Nov 15 
Trend analysis and forecasting, RapidMiner 
Critique due 
Nov 17 
Student presentation / discussion 
Project summary due 
Nov 22 
Thanksgiving 

Nov 24 
Thanksgiving 

Nov 29 
Rare class learning, multiclass learning 
HW #4 due 
Dec 1 
Transfer learning 
Critique due 
Dec 6 
Student presentation / discussion 

Dec 8 
Project presentations 

Dec 14 

Project report due 