After fixing my code and prepare my data for training I've found myself in front of 2 question.
Background: I have data made of date (one entry per minute) for the first column and congestion (value, between 0 and 200) for the 2nd. My goal is to feed it to my neural network and so be able to predict for the next week the congestion at each minute (my dataset is more than 10M of entry, I shouldn't have problem of lack of data for training).
Problem: I now have two question. First about the loss, optimizer and linear. It seem there is a certain number of them and they all have a domain where they are better than the other, which one would you recommend for this project? (Currently on my test I use Adam as an optimizer and mean_square as loss and linear for activation).
My second question is more like an error that I have (may be linked to me using the wrong loss/optimizer). When using my code (10 000 data of training for now) I have an accuracy of 0, a low loss (0.00X) and a bad prediction (not even close to the reality). Do you have any idea of where it could come from?