| January 7, 2003 |
Go over syllabus, Chapter 1: Introduction |
| January 9, 2003 |
Complete Chapter 1, k-nearest neighbor |
| January 14, 2003 |
K-nearest neighbor |
| January 16, 2003 |
Concept learning, discuss assignment |
| January 21, 2003 |
Concept learning, version spaces, bias |
| January 23, 2003 |
feature selection |
| January 28, 2003 |
Decision trees |
| January 30, 2003 |
Decision trees |
| February 4, 2003 |
Neural networks, HW 1 due |
| February 6, 2003 |
Neural networks |
| February 11, 2003 |
Support vector machines |
| February 13, 2003 |
Support vector machines |
| February 18, 2003 |
Evaluating hypotheses, HW 2 due |
| February 20, 2003 |
Evaluating hypotheses |
| February 25, 2003 |
Bayesian learning |
| February 27, 2003 |
Bayesian learning Midterm distributed |
| March 4, 2003 |
Bayesian learning, |
| March 6, 2003 |
Bayesian learning, Midterm due |
| March 11-13, 2003 |
Spring break |
| March 18, 2003 |
Computational learning theory |
| March 20, 2003 |
Student presentation of project topic, Project topics due |
| March 25, 2003 |
Computational learning theory |
| March 27, 2003 |
Computational learning theory |
| April 1, 2003/font> |
Instance-based learning |
| April 3, 2003 |
Genetic algorithms |
| April 8, 2003 |
Genetic algorithms |
| April 10, 2003 |
Guest lecture: Artificial immune systems, John Timmis, University of Kent |
| April 15, 2003 |
Reinforcement learning |
| April 17, 2003 |
Reinforcement learning |
| April 22, 2003 |
Ensembles of classifiers |
| April 24, 2003 |
Final distributed, Projects due |
| April 29, 2003 |
Wrap up |
May 6, 2003 |
Final due |
