I am not an expert at either neural nets in general or RNN’s but I have a data set that I would like to experiment with that is mostly time series in nature. I have roughly 30 different time series variables that I would like to use as my input in order to predict the classification of several classes

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As i’ve been looking into RNN’s, I only recently came across the concept of a GRU and from my initial thoughts it seems better suited to my particular task as I can specify which of the variables need something like a GRU unit and which do not. Is that even possible? For the variables that do not have a GRU I would like the longer term dependency to decay over the time series, thus I think I want to avoid LSTM.

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I am curious to hear if there are any best practices for using GRU or even deep RNN in general on time series classification. A lot of what I am reading re:RNN is related to NLP, which is an area I also like but quite different vs time series modelling.