Advice on models and processes for sequential data

Hello all,

I’m new to deep learning and am looking for some advice on models and processes to be using for my task.

I have sequential data consisting of eight variables at every time step as input; and the output is one variable, also at every time step.

I am starting with a simple RNN using LSTMs. Is there any other models or processes that I should be aware of that may improve performance?

Thanks very much!

Hi @stoops_ML ,
You may check the time series/ sequential data thread.
Another resource that may be of interest to you is tsai. It is a time series and sequential data open-source library built on top of Pytorch/ fastai. It contains a number of tutorial notebooks that may help get started.

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