If you just want to look at the examples, open any of the notebooks or the corresponding HTML exports in this repo.
If you want to start coding yourself, follow the installation procedures below to get started.
To get the notebooks in this tutorial running, we recommend using a Python installation via Anaconda.
We also recommend setting up a separate virtual environment. This bundles all the packages you need.
conda create -n ml-tutorial
conda activate ml-tutorial
Then, install the packages that will become your toolbox for this tutorial.
conda install numpy matplotlib skikit-learn jupyter
conda install pytorch torchvision -c pytorch
The last command is only necessary for the neural networks chapter.
git clone https://github.com/VLL-HD/ML-Tutorial
cd ML-Tutorial
To start the Jupyter notebook server, execute
jupyter notebook
A browser window will automatically open where you can view and edit the notebooks.
Script by Ullrich Köthe, code by Felix Draxler. Both at Visual Learning Lab, Heidelberg University.