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
- Install conda and run
conda env create -f environment.yml
- This will create
ml_with_sk
environment required to run the python notebooks available in thenotebooks
folder solutions
folder contains the answers to the quiz questionsfigures
folder contains the figures used in notebooksdatasets
contains the datasets used in notebooks