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. This course has been funded by Essential Data Science Training.