Foundational Machine Learning

I spend a lot of time working with LLMs these days that I need a refresher for the foundational machine learning models. So, I'm doing just that. I'll be posting my notes here (after a bit of clean-up). I hope this helps you if you're in the same journey or just starting out into Machine Learning. I'll try to explain a topic, the math behind it and also implement using numpy.

A lot of the variable naming and nomenclature is largely influenced by the resources I use. If something is not clear, add a comment.
A lot of this is a work in progress. So if you find an incomplete document or broken links, come back later.

What is Machine Learning?

There is a lot of content online that already cover this topic really well. This one is my [favourite](https://www.ibm.com/think/topics/machine-learning).