[IWantToRelocate]

Well, not much. Data isn't the main product where I work for, so I end up just using python libraries for some mundane applications and small datasets (image classification and recommender systems). But I'm the "need to know from scratch" kinda person and I wonder if I should waste my time learning the math behind it or if its useless

[PaulHoule]

What's the first derivative of

   x * cos(x)

?

[IWantToRelocate]

wolfram alpha told me its: cos(x) - xsin(x) lol kidding, i had calculus 15 years ago. so it sounds I should recap derivatives.

[PaulHoule]

This book is a little old but you should learn whatever math it takes to understand it

https://www.amazon.com/Networks-Recognition-Advanced-Econome...

Another oldie-but-goodie is

https://www.amazon.com/Neural-Networks-Lecture-Computer-Scie...

which tells the secret of when to stop when you're doing "early stopping", something I've seen many modern deep learners fail to get right.

Off the top of my head I would say the fundamental math about deep networks is not really new. Most of the work in that field is pretty ad-hoc and not a lot is proven; probably people that are proving things are using difficult graduate-level math but you don't need to go there.

[IWantToRelocate]

thank you Paul for the references, will def take a look mainly in the early stopping problem.