I am sorry for the mistakes I will make in this post, I'm new to deep learning ^^'
I am trying to build an LSTM model that can help me predict some unique value according to time series indices and previous time series indices correlated with the value.
To make it simple, I have an indice that varies throughout time and "place", it will be my input, and a resulting value (the output) that changes only once a year.
I thought of making this problem a classification problem, but the way I understood classification in this course, is to put (previously?) some values in an "output interval"
I have also tried to follow this tutorial, but I'm getting some weird results (since maybe I have changed the datetime into numeric data?), and a huge rmse of (above 70%)
Thank you for your time and advices:)