In this assignment, you'll get hands-on with a notebook which has a series of exercises based on the Scikit-Learn code and concepts we went through in the previous videos.
Download the Scikit-Learn exercises and solutions notebooks from GitHub and work through each cell in the exercises notebook using what you've learned in the previous videos.
Scikit-Learn Exercises Solutions notebook (avoid looking at this for as long as possible)
Don't forget, if you get stuck, there's plenty of help available!
Remember, you should always try to run the code yourself first.
If you're still stuck feel free to ask the Discord server (Checkout the #machinelearning-datascience channel for help) or search the internet for answers.
Note: In the notebook, there may be instructions to import a file from a file path such as "../data/car-sales.csv", you should change these to wherever you're storing "car-sales.csv". Or the direct link on GitHub (in raw format), such as, https://raw.githubusercontent.com/mrdbourke/zero-to-mastery-ml/master/data/car-sales.csv.
After working through the Scikit-Learn exercises notebook, how did you go?
Again, whether you blazed through them all or got stuck multiple times and had to look at the documentation or go back to the lectures, it's all part of the process.
Practising different exercises and writing code on your own is the best way to practice different concepts.