All notebook material: https://github.com/INRIA/scikit-learn-mooc/
A few different ways are available:
- Launch an online notebook environment using
- Browse website generated with Jupyter Book
The tutorials will require the following packages:
- python>=3.6
- jupyter
- scikit-learn
- pandas
- matplotlib
- seaborn
- plotly
- jupytext (required only for contributors)
We provide both requirements.txt and environment.yml to install packages.
You can install the packages using pip:
$ pip install -r requirements.txt
Alternatively, you can create an scikit-learn-tutorial conda environment
by executing:
$ conda env create -f environment.yml
then activate the environment with:
$ conda activate scikit-learn-tutorial
You can also update your current environment, instead of creating a new environment, using:
$ conda env update --prefix ./env --file environment.yml --prune
The source files, which should be modified, are in the python_scripts
directory. The notebooks are generated from these files.
This repository uses Jupytext to display Python files as notebooks. Saving as Python files facilitates version control.
When jupytext is properly connected to jupyter, the python files can be opened in jupyter and are directly displayed as notebooks
With jupyter notebook
Once jupytext is installed, run the following command:
jupyter serverextension enable jupytext
With jupyter lab
To make it work with "jupyter lab" (instead of
"jupyter notebook"), you have to install nodejs (conda install nodejs
works if you use conda). Then in jupyter lab you have to right click
"Open with -> notebook" to open the python scripts with the notebook
interface.
To update all the notebooks:
$ make
In some cases you
may need to use a jupytext command directly rather than using the provided
Makefile. For instance, to create a notebook from a Python script:
$ jupytext --to ipynb python_scripts/your_python_script.py --output notebooks/your_notebook.ipynb