We'll fully implement the ridge regression algorithm from scratch in python. Ridge regression is one of the most popular machine learning algorithms, and learning how it works can help you use it more effectively.
We'll cover what ridge regression is, including the theory and equation. Then we'll implement it in python and compare it to the reference implementation from scikit-learn. We'll end by learning how to calculate the optimal penalty lambda.
It's recommended to watch the video on linear regression before this one (https://youtu.be/z2hpinQggNM).
The full code and dataset are available here - https://github.com/dataquestio/project-walkthroughs/tree/master/ridge_regression .
Chapters
00:00 - Introduction
00:16 - Ridge regression overview
08:40 - Ridge regression equation
16:53 - Python implementation of the ridge algorithm
26:11 - Finding the optimal penalty
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