A single resource, in the form of a simple website built with GitHub Pages, which will hopefully serve as a complete crash course on the various areas of mathematics essential to understanding machine learning. To do this, I will use the Mathematics for Machine Learning Specialization on Coursera as my guide, but also pull from other resources, such as Khan Academy and 3Blue1Brown's various video playlists on Youtube.
The end goal will be to produce a simple site that someone (including myself) could use to quickly bring themselves up to speed on the fundamental mathematical concepts necessary for machine learning. The target audience are those who have at least some highschool math, but who should really have taken introductory courses on Linear Algebra and Calculus in college.
The website can be accessed here.
Full credit to the team behind the Mathematics for Machine Learning Specialization course on Coursera for creating such an awesome resource. I highly encourage anyone who needs to brush up on their mathematics for machine learning to check that course out.
Notebooks contains Jupyter notebooks for each course in the specialization, which each contain python implementations for many of the discussed concepts.
Just like the Mathematics for Machine Learning Specialization, This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
