if you have no mathematical background at all this isn’t the book for you i think. that is not really advanced mathematics although a little notationally dense.
there are many good materials such as the fantastic fast.ai course that don’t require such mathematical background.
if you are motivated to learn about ML, then studying the topic can gradually be a route in to more mathematical knowledge so that equations like this would not seem intimidating.
all I am saying is every deep learning book I have ever opened is filled with mathematical stuff like this. I want to learn the mathematics for it but I need a starting point. Isnt there atleast one book in the entire world written with this in mind?
"Dive Into Deep Learning" may be good in that it usually has code alongside any mathematical notation: https://d2l.ai/index.html
I have not actually looked at it in detail, but the legendary Gilbert Strang, in addition to his classic linear algebra course, also has a course that aims to teach enough linear algebra to explain deep learning called "Linear Algebra and Learning From Data". Maybe this is also helpful.
This is because the authors aren’t trying to teach you anything. They are trying to show how smart they are and make a name for themselves with their peers. They could care less whether you learn. Almost no one doing deep learning will learn much from this.
there are many good materials such as the fantastic fast.ai course that don’t require such mathematical background.
if you are motivated to learn about ML, then studying the topic can gradually be a route in to more mathematical knowledge so that equations like this would not seem intimidating.