How To Implement Simple Linear Regression From Scratch With Python

Last Updated on May 11, 2020

Linear regression is a prediction method that is more than 200 years old.

Simple linear regression is a great first machine learning algorithm to implement as it requires you to estimate properties from your training dataset, but is simple enough for beginners to understand.

In this tutorial, you will discover how to implement the simple linear regression algorithm from scratch in Python.

After completing this tutorial you will know:

• How to estimate statistical quantities from training data.
• How to estimate linear regression coefficients from data.
• How to make predictions using linear regression for new data.

Kick-start your project with my new book Machine Learning Algorithms From Scratch, including step-by-step tutorials and the Python source code files for all examples.

Let’s get started.

• Update Aug/2018: Tested and updated to work with Python 3.6.
• Update Feb/2019: Minor update to the expected default RMSE for the insurance dataset.