Generative models, M2 ENS 2025-2027
Class details are here.
Computational Optimal Transport for Machine and Deep Learning, M2 ENS 2024-2026
Class details are here.
Fundamentals of Machine Learning, M1 ENS 2024-2025
- Material for the Ensemble method class (26/02/2025) is here.
Optimization for large scale Machine Learning, M2 ENS 2022-2024
Class details are here.
Classes taught
Summer schools:
- OLISSIPO Winter school: dimensionality reduction with Titouan Vayer (02/2023)
- Convex optimization @Computation and Modelling summer school, WUST 2022 (intro slides and exercises)
Since my arrival at ENS de Lyon (Nov. 2021):
- 10 h on Fundamentals of Machine Learning (2024-2025), M1 Level.
- 36 h on optimal transport (2024-2026), M2 level, with Titouan Vayer and Quentin Bertrand.
- 2x36 h on large scale optimization for machine and deep learning (2022-2024), M2 level.
- 12 h on optimization (2023-2024), M1 level.
I am a part-time teacher at Polytechnique, where I teach the Python for datascience class (42 h per year since 2019) in the X/HEC “Datascience for business” Master, using live coding inspired by the Software Carpentry workshops. I designed the course from scratch, collaborating with Joan Massich in 2019, Quentin Bertrand in 2020, Hicham Janati in 2021, Sylvain Combettes in 2022 and Badr Moufad in 2023.
Since 2020 I teach and handle practical sessions and data camps in Ecole Polytechnique’s Executive education. Topics involved dimension reduction, clustering, scaling computations, visualization and datacamp. I designed 2 full python labs with Erwan Le Pennec on these topics.