dblabs-mcgill-mila / machine_learning_with_sklearn

Explore and understand the Machine Learning concepts through the prism of sklearn, one notebook at a time.

Machine Learning with scikit-learn

This course is derived from the June 2022 version of the brilliant work created by INRIA

We modified the reference content to suit the requirement of our team, where we conducted one training session per week and thus created a single self-contained notebook for respective machine learning/scikit-learn topic. These weekly training sessions ranged from 1 hour to 3 hours, and thus one can follow all the notebooks in roughly 10-18 hours, depending on their level of expertise.

We highly recommend enrolling in the original Machine learning in Python with scikit-learn MOOC

Importantly, we don't claim any copyrights on this material derived from the original work and have included references to all the other sources wherever used.

Credits, if any, rightly goes to Inria Learning Lab, scikit-learn @ La Fondation Inria and Inria Academy

How to setup/run and other notes on your local machine

1. Install conda and run conda env create -f environment.yml
2. This will create ml_with_sk environment required to run the python notebooks available in the notebooks folder
3. solutions folder contains the answers to the quiz questions
4. figures folder contains the figures used in notebooks
5. datasets contains the datasets used in notebooks