Fiches de cours

Statistical machine learning

MATH-412

Enseignant(s) :

Obozinski Guillaume Romain

Langue:

English

Summary

A course on statistical methods for supervised and unsupervised learning.

Content

Learning Prerequisites

Required courses

Analysis, Linear Algebra, Probability and Statistics, Linear Models

Important concepts to start the course

This is a statistics/mathematics course. Prior to following this course, the student must have very good knowledge of basic probabilty and statistics (statistical modeling and inference, linear regression).

Learning Outcomes

By the end of the course, the student must be able to:

Teaching methods

Ex cathedra lectures, exercises and computer practicals in the classroom and at home.

Assessment methods

Written final exam (70%) + Project of implementation or application on real data of a model/algorithm based on a classical research paper describing an important method from the literature. (30%)

Seconde tentative : Dans le cas de l'art. 3 al. 5 du Règlement de section, l'enseignant décide de la forme de l'examen qu'il communique aux étudiants concernés.

Resources

Bibliography

Ressources en bibliothèque
Notes/Handbook

A polycopié will be available on Moodle.

Dans les plans d'études

Semaine de référence

 LuMaMeJeVe
8-9  MAA331  
9-10    
10-11   MAA112 
11-12    
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     
 
      Cours
      Exercice, TP
      Projet, autre

légende

  • Semestre d'automne
  • Session d'hiver
  • Semestre de printemps
  • Session d'été
  • Cours en français
  • Cours en anglais
  • Cours en allemand