In this project, we'll build a ridge regression algorithm from scratch. We'll cover what ridge regression is, how it works, and how to implement it 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 create our algorithm using python and pandas. We'll then compare it to the reference implementation from scikit-learn.
It's recommended to watch the video on linear regression before this one.
You can find the code for this project here.
File overview:
ridge_regression.ipynb- the full code from this project
To follow this project, please install the following locally:
- Python 3.8+
- Python packages
- pandas
- numpy
- scikit-learn
We'll be using data from the Olympics, which was originally on Kaggle.
You can download the file we'll use in this project here:
- teams.csv - the team-level data that we use in this project.