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Sorry I'm new to machine learning and statistics.

For time series predictions, do you use RNN or something? For example, the past 2 years' sales of a product.

TBH Im pretty much unfamiliar with how statisticians deal with time series data.

I'm dealing with some time series problems and I'm not sure if I should put all my trust on RNN or some other DL models.

What do you think of the RNN models? I mean if it works fine then I dont have to research on other models

Sorry I'm unable to provide the specific data here, don't know if it will cause vagueness. But the sales data is definitely a topic of interest.

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Choosing which model to use depends on your goal and the data you have. Experimenting with different models is always a good idea. I assume you are trying to predict sales based on previous sales. In this case, RNN will probably do the job. I strongly suggest researching the LSTM layer - once you read about it and its results you will understand why I strongly suggest it. If you do not have time to experiment with different models, I suggest at least experimenting with different features. You can try including/excluding features that you have available.

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