This repository contains a Jupyter notebook that explores regularized linear regression. The algorithms are based off of a Kaggle dataset. The data is included in the repository, but you can follow the Task (PDF file) description if you would like to follow along at the Kaggle URL.
This repository aims to demonstrate a well-rounded understanding of linear regression. If you can follow along with the notebook, you understand the process one goes through when it comes to linear regression. The purpose of this repository is NOT to achieve great results, NOT to do everything perfectly, but instead to show basic linear regression in an easy to understand way. You will find comments exploring and explaining parts of the project embedded within. Enjoy!