Machine Learning

UE: Machine Learning, Apprentissage Automatique
Responsable(s), établissement(s) Michele Sebag, Alexandre Allausen, Université Paris Sud
Adresse(s) mail,
Lieu principal d’enseignement Université Paris Sud
ECTS 2.5
Nombre d’heures total 21
Cours 15
TD 6
TP 0
Objectives To acquaint the students with the principles and main algorithms in Machine Learning.
The students will also acquire the practice of some ML environments (e.g. scikit-learn in Python).
  • Generalities: representation, loss function, generalization, overfitting, entropy
  • Bayesian reasoning (naïve Bayes, Expectation Maximization, clustering)
  • Linear discrimination and Support Vector Machines
  • Neural Nets and Deep Learning
Language English