Page du cours

Réseaux de Neurones profonds pour l'Apprentissage

(année 2023-2024)

Master 2 Statistique & Data Science, Ingénierie Mathématique

• Logiciels: Python et PyTorch (et autres bibliothèques (libraries): numpy, matplotlib, scikit-learn,...)
• Les supports de cours sont en anglais, les cours en français.

Séance 1

• Course slides on Introduction to Artificial Neural Networks for image classification (.pdf)
• Practice session on logistic regression: Chose notebook and click on open in Colab

Séance 2

• Course slides on Introduction to Artificial Neural Networks for image classification: Backpropagation and CNN(.pdf)
• Course slides on Introduction to Artificial Neural Networks for image classification: Deep learning and CNN (.pdf)
• PyTorch tutorial

Séance 3

• Course slides on Introduction to Artificial Neural Networks for image classification: Deep learning recipes (.pdf)

Séance 4

• PyTorch practice session on transfer learning: Chose notebook and click on open in Colab

Séance 5

• Course slides on Generative Models (.pdf)

Séance 6

• PyTorch practice session on GANs: Chose notebook and click on open in Colab
• Course slides on Texture Synthesis and Style Transfer (.pdf)
• Notebook on style transfer

Séance 7

• End of course and final project.