I could not believe the response I got for my previous blog post learning maths for Machine Learning and Deep Learning. There are definitely lots of people like me, who are interested in learning math in greater depth. I’ve returned in 2018 with an updated list because I’ve been totally blown away by resources I’ve recently discovered.
The Essence of Linear Algebra (YouTube)
3Blue1Brown has created an amazing youtube video series entitled “The Essence of Linear Algebra”. The series of videos are highly visual and 3Blue1Brown explains linear algebra concepts from a geometric perspective. I must admit that 3Blue1Brown offers explanations and intuitions on linear algebra that I’d wish were taught in all books and lectures. I certainly found myself wishing that I’d had this resource way back when I was a first year engineering student. The custom animations are programmed in Python by 3Blue1Brown.
The Essence of Calculus (YouTube)
“The Essence of Calculus” is another gem from 3Blue1Brown. Also a youtube video series with custom animations, the series will make you feel like youdiscovered Calculus.
The Matrix Calculus You Need For Deep Learning (Online)
Terence Parr and Jeremy Howard (yes thats the same Jeremy Howard from fast.ai fame) explain Matrix Calculus from first principles. If you have programmed a neural network and implemented back propagation, this resource is the next step in completely understanding the underpinning mathematics.
Mathematics for Machine Learning (Book)
Still a work in progress book but chapters for Analytical Geometry, Linear Algebra and Vector Calculus look intuitive and comprehensive.
That’s all for the moment. Please share any useful resources you find in the comments. All the best in your Math travels….
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