NEWSLETTER
A tutorial about how a linear regression model can be implemented in Python without using automatic learning libraries to obtain a deeper understanding of how underlying mathematics operates
The data used in this article have a license under a Creative Commons license and is allowed for commercial use
With all the emotion and energy around ai, it is easy to lose sight of all the fundamental mathematics and technology that gives it life. As a professional in the field, you can improve significantly or renew your understanding of these underlying techniques by encoding a model without using automatic learning libraries such as Sklearn, Tensorflow, Pytorch and many more.
This inspired me to start a new series called DIY ai. We will immerse ourselves in several automatic learning models and build them from scratch. At the end of each article, its objective is that the reader has an extremely deep and fundamental understanding of the models we build and use daily as data professionals. Let's start with things Multiple linear regression.
