2008I Departamento de Ingeniería de Sistemas e Industrial Universidad Nacional de Colombia 
Ing. Fabio A. González O., Ph.D. Of. 114, Edif. Nuevo de Ingeniería fagonzalezo_at_unal.edu.co 
Topic  Material  Assignments  Presentations 

1. Introduction 
Brief
Introduction to ML (notes) [Mit97] Cap 1 [Alp04] Cap 1,2 [DHS00] A.1, A.2 
Assignment
1 
Videos: The great robot race Introduction to ML (notes) 
2. Bayesian decision theory 2.1 A review of probability theory 2.2 Classification 2.3 Lost and risk 2.4 Naive Bayes classifier 2.5 Bayesian Networks 2.6 Maximum likelihood estimation 2.7 Bayesian estimation 2.8 Parametric Classification 2.9 Expectation Maximization 
[Alp04] Chap 3 (notes) Chap 4 (notes) Chap 7 (Sect. 7.4) (EM notes) (Parametric notes) [DHS00] Chap 3 [Tenenbaum06] 
Assignment
2 Assignment 3 
Video: Graphical models (notes) Paper presentation: [Friedman99] Alejandro Riveros [Goldenberg05] Camilo López [Dietterich02] Jeison Gutierres 
3. Kernel methods 3.1 The kernel trick 3.2 Kernel ridge regression 3.3 Kernel functions 3.4 Other kernel Algorithms 3.5 Kernels in complex structured data 
[SC04] Chap 2 Introd. to kernel methods (notes) Matlab examples (.pdf,.m) 
Video: Support Vector Classification (part 4) Paper presentation: [Grauman05] María E. Rojas [Lodhi02] David Becerra [Leslie02] Daniel Restrepo 

4. Regularization and model complexity 4.1 Bias vs variance tradeoff 4.2 Risk and empirical risk 4.3 Complexity measures 
Chap
4 (Sect. 4.3, 4.7, 4.8) (bias/var notes) 
Assignment 4  Video: Iterative Regularization Scheme and Early Stopping in Learning from Examples Paper presentation: [Roberts00] José Luis Morales [Lawrence96] Javier Vargas [Mehta95] Alexander Cerón 
5. Performance evaluation 5.1 Performance evaluation in supervised learning 5.2 Performance evaluation in unsupervised learning 5.3 Hypthesis testing 
[Alp04] Cap 14 [TSK05] Chap 8 (Sect. 8.5) 
Assignment 5  Video: An Empirical Comparison of Learning Methods and Metrics Paper presentation: [Hand01] Carlos Garzón [Domingos99] Jimmy Cifuentes [Japkowicz02] Omar Erazo 
6. Combining multiple classifiers 6.1 Voting 6.2 Error correcting codes 6.3 Bagging 6.4 Boosting 
[Alp04] Cap 15 
[Dietterich00] Sandra Tocarruncho [Oza05] Emir Cortés [Mason00] Edwin Niño 

7. Clustering and density estimation  Miguel Dussan: Web Clustering Rolando Beltrán: BiClustering Wilson Soto: Sequence Clustering 

Final Exam (19/6/08)  
Project (08/7/08) 