Teaching

Master MIA – University Paris-Saclay (current)

• Introduction to Deep Learning
  • Session 1 – Generalities: slides – perceptron convergence
  • Session 2 – Neural Network Estimation: slides
  • Session 3 – Hyperparameter Selection: slides
  • Session 4 – Convolutional Networks: slides
  • Session 5 – Generative Networks: slides
  • Session 6 – Recurrent Networks: slides
  • Session 7 – AI & Ethics: slides – mind map
• Generative Models
  • Session 1 – Generalities: slides
  • Session 2 – Autoregressive Models: slides – recording
  • Session 3 – VAE & Normalising Flows: slides – tutorial – correction
  • Session 4 – Generative Adversarial Networks: slides
  • Session 5 & 6 – Diffusion Models: slides

University Paris-Saclay (past)

• Machine Learning Algorithms
  • Session 1 – Feature Engineering and SVM: slides – tutorial
  • Session 2 – Random Forest: slides – tutorial
  • Session 3 – Boosting: slides – tutorial
  • Session 4 – Unsupervised Learning: slides
  • Session 5 – Project Session 1
  • Session 6 – Project Session 2

ENSAE (past)

• Statistics 1 with Arnak Dalalyan
• Introduction to Machine Learning with Vianney Perchet

ENSTA (past)

• Time Series with Yannig Goude