Deep Neural Networks
Slides for the course: [Epita] Deep Neural Networks Course:
- Introduction
- Back Propagation
- Convolutional Neural Networks
- Detection / Segmentation
- Generative Models
- Transformers and MLP-Mixers
- Videos
- DALL-E 2
- Overview
NERF tutorial: gitlab page
These slides are based on another course by Olivier Grisel and Charles Ollion.
Notebooks for the course: [Epita] Deep Neural Networks Course:
wget https://deepcourse-epita.netlify.app/notebooks/Backpropagation_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/Autograd_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/Convolutions_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/CNN_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/Transfer_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/Localization_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/Segmentation_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/Metric_Learning_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/Domain_Adaptation_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/VAE_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/GAN_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/Transformer_Deepcourse.ipynb
wget https://deepcourse-epita.netlify.app/notebooks/MLP_Mixer_Deepcourse.ipynbThese notebooks are based on the material provided by Arthur Douillard.