Coverage of least squares modeling in pure python without numpy or scipy built up from previous blog posts from https://integratedmlai.com/.
Our goal is to better understand principles of machine learning tools by exploring how to code them ourselves ...
Meaning, we are seeking to code these tools without using the AWESOME python modules available for machine learning.
These efforts will provide insights and better understanding. This post stands on the shoulders of the posts before it, and presents our first real machine learning tool.
At one end of the spectrum, if you are new to linear algebra or python or both, I believe that you will find this post helpful among, I hope, a good group of saved links.
At the other end of the spectrum, if you have background with python and linear algebra, your reason to read this post would be to compare how I did it to how you'd do it. The review may give you some new ideas, or it may confirm that you still like your way better.
Please find the blog post related to this repo at https://integratedmlai.com/least-squares:-math-to-pure-python-without-numpy-or-scipy
I would appreciate it, as you share your work leveraged from this set of scripts, if you would please keep a referral back to my github repo. Thanks! I'd do the same for you. :-)
I am open to share the development and improvements of this with others, but it has been solo up until now. Let me know if you'd like to contribute.
This work came from originally.
"The code in this project is licensed under MIT license."