ML From Scratch: Linear, Polynomial, and Regularized Regression Models

In this new series, I took it upon myself to improve my coding skills and habits by writing clean, reusable, well-documented code with test cases. This is the first part of the series where I implement Linear, Polynomial, Ridge, Lasso, and ElasticNet Regression from scratch in an object-oriented manner. We'll start with a simple LinearRegression class and then build upon it creating an entire module of linear models in a simple style similar to Scikit-Learn. My implementations are in no way optimal solutions and are only meant to increase our understanding of machine learning. In the repository you will find all of the code found in this blog and more including test cases for every class and function.