Is there some guideline to designing architecture for neural networks?
I want to use LSTM network for predicting in time series. I have a small dictionary variation (8 values) but lot of their combinations.
How do I know how many memory block assemblies, how many memory cells each, input gates, forget gates, output gates and so on?
I am totally newbie, never used LSTM. I am in the very first phase - only research so far.