EuroSciPy 2019 - scikit-learn tutorial

All notebook material: https://github.com/lesteve/euroscipy-2019-scikit-learn-tutorial/

Some intro slides: http://ogrisel.github.io/decks/2017_intro_sklearn

Follow the tutorial online

• Launch an online notebook environment using

• Browse the static content online (pre-rendered outputs) using nbviewer

You need an internet connection but you will not have to install any package locally.

Running the tutorial locally

Dependencies

The tutorials will require the following packages:

• python>=3.6
• jupyter
• scikit-learn
• pandas
• pandas-profiling
• matplotlib
• seaborn

Local install

We provide both requirements.txt and environment.yml to install packages.

You can install the packages using pip:

$ pip install -r requirements.txt

You can create an sklearn-tutorial conda environment executing:

$ conda env create -f environment.yml

and later activate the environment:

$ conda activate sklearn-tutorial

You might also only update your current environment using:

$ conda env update --prefix ./env --file environment.yml  --prune

Contributing

This repo uses: Jupytext doc

To synchronize the notebooks and the Python scripts (based on filestamps, only input cells content is modified in the notebooks):

$ jupytext --sync notebooks/*.ipynb

or simply use:

$ make sync

If you create a new notebook, you need to set-up the text files it is going to be paired with:

$ jupytext --set-formats notebooks//ipynb,python_scripts//py:percent notebooks/*.ipynb

or simply use:

$ make format

To render all the notebooks (from time to time, slow to run):

$ make render

Direct binder links to GKE and OVH to trigger and cache builds

• GKE Binder

• OVH Binder