Refrence to learn all about math details RNNs backprobs

Hi. does any body know a good refrence for RNNs backprobs?

What is a “backprob”?

Here’s a bibliography thread that points to a lot of books. You can take a look there and some of them are more mathematical.

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Thanks. Is it worth learning all the math behind backpropagation of rnns?

Backpropagation. typo! sorry:)

It depends on what your goals are. If you want to be able to build working solutions to problems using ML/DL techniques, you don’t really need to know the details of how backpropagation works. That is handled for you by the various platforms like TensorFlow and PyTorch and so forth. The code is already written for you and you can apply it successfully without knowing what is going on in the code.

But if your goal is to become an ML/DL researcher and advance the algorithmic state of the art, e.g. by discovering new techniques that eventually become APIs in TF or PyTorch, then it probably would be relevant to understand the underlying math.

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