Please use the dedicated forum on moodle for questions on theory and exercises.
If you notice some errors in the notebooks/homeworks contact me at: name@phd.units.it (name=ginevra.carbone)
- Stackexchange
- Github guide
- Virtualenvs in python3
- Beginners numpy tutorial
- Beginners pandas tutorial
- Pyro 1.2.1 documentation
Code runs on python 3.6.9 and torch 1.4.0.
Download, clone or fork (your choice) this repository in a directory PATH_TO_DIR/.
Create a virtual environment using python3 (commands are provided for Debian-like GNU/Linux distributions)
cd PATH_TO_DIR/statistical-machine-learning/
sudo apt-get install python3-pip
python3 -m pip install --user virtualenv
python3 -m virtualenv -p "$(which python3)" venv
Now you should see PATH_TO_DIR/statistical-machine-learning/venv/ folder.
Activate the enviroment and install the requirements:
source venv/bin/activate
python3 -m pip install -r ./requirements.txt
Register the just-installed virtual environment for use with Jupyter:
python3 -m ipykernel install --user --name statistical-machine-learning --display-name "Python (SML virtualenv)"
Open your notebooks using jupyter-notebook (or jupyter-lab):
python3 -m jupyter notebook
To deactivate the environment use source deactivate command.