Machine learning

Description

Objectifs

At the end of this module, the student will have understood and be able to explain (main concepts):

-Main concepts and risks of machine learning.
-Advanced methods of machine learning on vector data, requiring tuning effort and/or expert knowledge.
-Ethics of artificial intelligence.

At the end of this module, the student should be able to:

-Solve simple exercises about the underlying mathematical theory.
-Put in action the data science methodology on case studies with R and Python.
-Explain to non-experts the tuning choices in the algorithms.
-Criticize the assumptions and results, summarize the main conclusions.
-Detect legal defects (bias, discrimination) in the algorithms.

Pré-requis

Course « Data science »
Course « Generalized linear model »

Évaluation

L’évaluation des acquis d’apprentissage est réalisée en continu tout le long du semestre. En fonction des enseignements, elle peut prendre différentes formes : examen écrit, oral, compte-rendu, rapport écrit, évaluation par les pairs…