Coursebooks 2018-2019

PDF
 

Machine Learning for Engineers

EE-613

Lecturer(s) :

Calinon Sylvain
Fleuret François
Odobez Jean-Marc

Language:

English

Frequency

Every 2 years

Remarque

Every two years. Next time: Fall 2019

Summary

The objective of this course is to give an overview of machine learning techniques used for real-world applications, and to teach how to implement and use them in practice.

Content

Fundamentals

Generative models

Regression

Discriminative models

Meta-algorithms

Keywords

Machine learning, pattern recognition, regression.

Learning Prerequisites

Required courses

At least one prior course in probabilities, linear algebra and programming (C, Java or equivalent).

Learning Outcomes

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

Assessment methods

Multiple.

 

In the programs

Reference week

 
      Lecture
      Exercise, TP
      Project, other

legend

  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German