#  Date  Teacher  Title 

1  05/02/2019  A. Rudi
P. Gaillard 
Introduction
TD0 (Python test file) 
2  12/02/2019  P. Gaillard
R. Berthier 
Linear regression
TD1 (Data: classificationA_train, classificationA_test, classificationB_train, classificationB_test, classificationC_train, classificationC_test, mnist_digits.mat), solution 
3  19/02/2019  A. Rudi
R. Berthier 
Statistical properties in ML
solution 
4  26/02/2019  A. Rudi
R. Berthier 
KNN
TD2, solution 
05/03/2019  Vacation  
5  12/03/2019  P. Gaillard
R. Berthier 
Logistic regression and convex analysis
TD3, solution 
6  19/03/2019  A. Rudi
R. Berthier 
Convex optimization (good slides from AurĂ©lien Garivier, GD smooth and strongly convex, SGD)
TD4, solution 
26/03/2019  No class  
7  02/04/2019  P. Gaillard
R. Berthier 
High dimensional statistics
TD4, solution  first assignment available 
8  09/04/2019  P. Gaillard
R. Berthier 
Model based machine learning: maximum likelihood
TD5, data, solution 
9  16/04/2019  A. Rudi
R. Berthier 
Kernels (good notes from Arthur Gretton, sections 1, 2, 6)

23/04/2019  Vacation  
30/04/2019  Vacation  
10  07/05/2019  P. Gaillard
R. Berthier 
Unsupervised learning
TD7  first assignment due date and second assignment available 
11  14/05/2019  A. Rudi
R. Berthier 
Neural networks
TD8  solution 
12  21/05/2019  A. Rudi
R. Berthier 
Summary
Last semester exam, solution  second assignment due date 
13  28/05/2019  P. Gaillard  Exam 