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DIY AI & ML: How to Build a Linear Regression Model from Scratch
A walkthrough on how one can implement a linear regression model in Python without using machine learning libraries to gain a more in-depth understanding of how the underlying mathematics work
The data used in this article is licensed under a creative commons license and is permitted for commercial use
Introduction
With all of the excitement and energy around AI, it is easy to lose sight of all the foundational mathematics and technology that brings it to life. As a professional in the field, you can significantly enhance or renew your understanding of these underlying techniques by coding a model without using machine learning libraries such as sklearn, TensorFlow, PyTorch, and many more.
This inspired me to start a new series called DIY AI. We will dive into various machine-learning models and build them from the ground up. At the end of each article, I aim for the reader to have an extremely in-depth and foundational understanding of the models we build and use daily as data professionals. Let’s get things started with Multiple Linear Regression.
