Course material for a ~3 * 15 hours (5 ECTS) course on basic concepts for data science. All the topics are presented with the Python implementation included. We cover matrix decompositions, regression, signal processing, sparsity and compressed sensing and a bit of statistics.
We use Quarto to generate the lecture material.
Where we are creating a book, see docs for the structure.
In short, each part has its own folder where you find the qmd files and everything is managed via _quarto.yml.
In order to make the use easy the entire project is managed with pdm so to start the preview run
pdm sync
pdm quarto previewThe project is also compatible with the VSCode extension of Quarto, just make sure the the Python environment in ./.venv is used.
Important
In one example locale.setlocale(locale.LC_ALL, 'de_AT.utf8') is used so make sure the language is installed on your system to make this example run.
After pushing the published website will automatically be built and deployed at kandolfp.github.io/MECH-M-DUAL-1-DBM/. Due to the dynamic nature of the material this might take a couple of minutes.
You can also create a pdf by calling
pdm run quarto render --to pdf
or the html version
pdm run quarto render --to html
You can also find a pdf in the releases