Webpage for the doctoral course

Introduction to Deep Learning

Bruno Galerne, University of Orléans

Collège doctoral Centre-Val de Loire

• Software: Python and PyTorch via Google Colab.
• Course on MS Teams (see link send by email).

Day 1

• Slides Introduction to Artificial Neural Networks (.pdf)
• Slides Deep Neural Networks and Convolutional Neural Networks (CNN) (.pdf)
• Practice session: PyTorch tutorial.

Day 2

• Slides Deep Learning Recipes and Standard Models (.pdf)
• Practice session: Transfer Learning for Computer Vision

Day 3

• Slides on generative models (.pdf)
• Practice session: Vanilla GAN

Day 4

• Material on Transformers:
  • Binxu Wang’s “Transformers:Architecture, Training & Usage” (Machine Learning from Scratch) (.pdf)
  • Lucas Beyer’s Full Transformer tutorial slides (Google slides)
• Slides on diffusion models (.pdf)
• Practice session: Diffusion model sampling