Hello. I have a dataset with 1500 time series with 900 individual time steps and 300 features for each time step. I would like to use the data for a network that starts with an embedding layer that then feeds into a RNN for sequence learning (option 1).
Alternatively (option 2) I could train a standard NLP with an embedding layer and then feed that output into a different network with RNN layers if the first option is not possible. Would you be able to descrive what shape/format the data needs to have for this to work?