These are some notes that I put together for myself when going through Andrew Ng's famous Coursera class on Machine Learning.
I've also included a pdf that has some matrix calculus basics. I no longer remember if this was mentioned in the class or not, but I found it helpful.
Feel free to submit issues if you find any typos/errors in this (which I'm sure there are plenty of).