The course uses Python 3 and some data analysis packages such as Numpy, Pandas, scikit-learn, and matplotlib.
This step is only necessary if you don't have conda installed already:
- download the Miniconda installer for your operating system (Windows, MacOSX or Linux) here
- run the installer following the instructions here depending on your operating system.
# Clone this repo
git clone https://github.com/INRIA/scikit-learn-mooc
cd scikit-learn-mooc
# Create a conda environment with the required packages for this tutorial:
conda env create -f environment.yml
To make sure you have all the necessary packages installed, we strongly
recommend you to execute the check_env.py
script located at the root of
this repository:
# Activate your conda environment
conda activate scikit-learn-course
python check_env.py
Make sure that there is no FAIL
in the output when running the check_env.py
script, i.e. that its output looks similar to this:
Using python in /home/lesteve/miniconda3/envs/scikit-learn-course
3.9.1 | packaged by conda-forge | (default, Jan 10 2021, 02:55:42)
[GCC 9.3.0]
[ OK ] numpy version 1.19.5
[ OK ] scipy version 1.6.0
[ OK ] matplotlib version 3.3.3
[ OK ] sklearn version 1.1.1
[ OK ] pandas version 1.2.0
[ OK ] seaborn version 0.11.1
[ OK ] notebook version 6.2.0
[ OK ] plotly version 4.14.3
# Activate your conda environment
conda activate scikit-learn-course
jupyter notebook full-index.md
full-index.md
is an index file helping to navigate the notebooks.
All the Jupyter notebooks are located in the notebooks
folder.