Performing Linear Regression Using the Normal Equation in most simplified version

I recently wrote a beginner-friendly article about performing linear regression using the Normal Equation.

I tried to explain the idea step by step, starting with a simple question:

If some coefficients can minimize the prediction error, how can we find them?

From there, I introduced the Normal Equation and showed how the formula works:

I also implemented the main matrix operations in Python instead of treating the formula as a black box.

The goal was not only to use linear regression, but to understand what is happening behind the formula and how the mathematics connects to the code.

If you are learning machine learning and want to understand linear regression from the basics, you may find the article useful.