In this project, we'll build a linear regression algorithm from scratch. Linear regression is the most popular machine learning model. Understanding how it works can help you apply it more effectively.
We'll create our algorithm using python and pandas. We'll then compare it to the reference implementation from scikit-learn.
You can find the code for this project here.
File overview:
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.