Machine learning basics

Machine learning basics

"Learning the basics of machine learning using Jupyter Notebook."


The estimated time to complete this training module is 4h.

The prerequisites to take this module are:

Contact Désirée Lussier if you have questions on this module, or if you want to check that you completed successfully all the exercises.


The tutorial slides and video portion of this module were presented by Estefany Suarez and Jacob Vogel during Brainhack School 2020.

The tutorial slides are available here.

The notebook for the exercise is available here

The video presentations are available below. The first video (Estefany Suarez and Jacob Vogel) is here:


  • Watch the video presentation by Estefany Suarez and go over the slides.
  • Download the notebook
  • Follow the tutorial within the Jupyter Notebook and run the code. Feel free to play around with the code to see what happens!
  • Follow up with Désirée Lussier to validate you completed the exercise correctly.
  • 🎉 🎉 🎉 you completed this training module! 🎉 🎉 🎉

More resources

Want to dive deeper into machine learning?

If you are curious to learn more, you can check this tutorial “Understanding and diagnosing your machine-learning models” by Gael Varoquaux here.

You can also take a look at the MAIN 2021 educational tutorial on model selection & validation as well as supervised learning notes here

Additional examples, tutorials, and documentation can be found at the Scikit-Learn website.