91o291o

91o291o t1_j0153r3 wrote

Most DL books have an appendix with the linear algebra and calculus needed to understand what's in the book.

I've not seen it yet, but maybe you can take a look at the new course by Sebastian Raschka on the ligthning website?

I can't help with calcululs and algebra because I already know those subjects, so I can't tell you where to study such notions...

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91o291o t1_izwdjgr wrote

There's no way that you can understand DL unless you're proficient with some basic calculus (matrix multiplications, rank of a matrix, norms etc). You don't need to be good at math, but you really need to understand some concepts.

If you don't understand math, you won't improve, you will be just "imitating" people who know those concepts. You will be able to delay your complete failure, anyway.

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91o291o t1_iz8uvlz wrote

Each and every book about ML and deep learning has some important references to papers.

Just skim such books and find those important references you need. For example the latest Sebastian Raschka book from 2022 about Machine Learning is very good and cites milestones paper.

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