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Environment setup for the introduction to Machine Learning Course

❗ if you encounter any error with the instructions given on this page, please create a github issue to explain your problem and we will try to get back to you ASAP.

We detail in this page how to set up your environment with the different external modules you will need in order to be able to follow the course.

We recommend you create a new conda environment specifically for the course (if you are unfamiliar with conda environment see this documentation).

Nevertheless, we detail here several methods a trust you will choose the one most appropriate to your situations.

important: the course materials were developped and tested with python >3.8 and scikit-learn >1. Any anterior version will give errors and warnings aplenty!

NB: for future reference, as of july 2022, the material has been tested with python 3.10.5 and scikit-learn 1.1.1

method 1 : new conda environment from .yml

Download the file introML2022.yml.

If you are on Windows and/or are allergic to command line, you can use the anaconda navigator (if you don't know how to start the navigator, here's how).

Otherwise, just open a terminal, navigate to where the file is, and use the following command:

conda env create -f introML2022.yml

Activate the new environment: conda activate introML2022

Verify that the new environment was installed correctly: conda env list

method 2 : conda and pip commands to install

These first 2 commands create and activate a new enviroment

conda create --name introML2022 python=3.10.5
conda activate introML2022

These commands install all necessary modules and their dependencies:

conda install -c conda-forge scikit-learn
pip install notebook
conda install seaborn
pip install xlrd
pip install openpyxl
conda install -c anaconda graphviz
conda install -c anaconda pydotplus
pip install string-kernels
conda install pytorch torchvision torchaudio cpuonly -c pytorch

conda install command will prompt you for confirmation before installing once they have retrieved the dependencies.

method 3 : install the following however you want

Python : at least 3.8

  • scikit-learn (version ar least 1.0)
  • jupyter-notebook
  • seaborn
  • xlrd
  • openpyxl
  • graphviz
  • pydotplus
  • string-kernels
  • pytorch