
This class is about the main techniques of reinforcement learning:
- Markov decision process
- TD learning
- Q learning
- Bandit algorithms
- Monte-Carlo tree search
Applications to e-commerce will be considered.
- Teacher: Thomas Bonald
- Teacher: Claire Vernade
- Teacher: Till Wohlfartht

Main techniques for machine learning in high dimension.
- Teacher: Thomas Bonald
- Teacher: Simon Delarue
- Teacher: Charlotte Laclau
- Teacher: Till Wohlfartht
This course is part of the Graduate Degree in Artificial Intelligence. It treats the automated processing of natural language - in the form of text and speech. The course is given by Chloé Clavel and Fabian Suchanek.
The
course consists of 4 parts, each with a morning session (9:15-12:30
with 15min break) and an afternoon session (13:30-16:45). The afternoon
session is lab
work. The final grade of the course is computed as the average of the
grades of the labs. Labs are done alone. Plagiarism is sanctioned by a
grade of 0/20.
The lab material is intended only for the participants of this course, and may not be shared publicly.
- Teacher: Lihu Chen
- Teacher: Chloé Clavel
- Teacher: Matthieu Labeau
This course is part of the Master of Science and Technology in Artificial Intelligence. It treats the automated processing of natural language - in the form of text and speech. The course is given by Chloé Clavel and Fabian Suchanek.
The
course consists of 4 parts, each with a morning session (9:15-12:30
with 15min break) and an afternoon session (13:30-16:45). The afternoon
session is lab
work. The final grade of the course is computed as the average of the
grades of the labs. Labs are done alone. Plagiarism is sanctioned by a
grade of 0/20.
The lab material is intended only for the participants of this course, and may not be shared publicly.
- Teacher: Emile Chapuis
- Teacher: Chloé Clavel
Le traitement automatique des langues est un domaine en pleine expansion. Par exemple, beaucoup d'efforts ont été récemment consacrés au développement de méthodes capables d'analyser les données d'opinion disponibles sur le Web social. Le premier objectif de ce cours est d'aborder les différentes méthodes de traitement de la langue et d'apprentissage automatique sous-jacentes à l'analyse des textes. Au cours de ce cours, les étudiants acquerront des compétences théoriques et techniques sur les méthodes avancées d'apprentissage automatique et le traitement du langage naturel.
Les techniques et concepts qui seront étudiés comprennent:
-processus de langage naturel: tokenisation, marquage de partie de discours, représentation de document et word embeddings
ressources linguistiques : les lexiques, wordnet
-classement de texte et catégorisation de texte: méthodes avancées d'apprentissage automatique telles que les réseaux de neurones, les modèles markov cachés, etc.
- Teacher: Chloé Clavel
- Teacher: Matthieu Labeau
- Teacher: Lihu Chen
- Teacher: Chloé Clavel
- Teacher: Tanvi Dinkar
- Teacher: Julien Romero
- Teacher: Fabian Suchanek
- Teacher: Samuel Tardieu
- Teacher: Etienne Borde
- Teacher: Eric Lecolinet
- Teacher: Thomas Robert