⚠️ This course has been superseded by mlr3torch-course. Please refer to that repository for the most up-to-date material.
This is a course, containing seven tutorials and corresponding exercises with solutions on torch and mlr3torch.
The seven topics are:
- Torch Tensors
- Autograd
- Modules and Data
- Optimizers
- Intro to mlr3torch (and mlr3 recap)
- Training Efficiency
- Use Case (WIP)
After editing the content, e.g. in the notebooks folder, run quarto render to render the website.
This will render the website into the docs/ folder.
Upon pushing the changes to GitHub, the content of the docs/ folder is automatically deployed to GitHub Pages.
Some of the content is based on the book Deep Learning and Scientific Computing with R torch by Sigrid Keydana.