I have data of 2000 stores with associated 145 features (example: ambience, holidays, no. of brands) and their monthly sales for 2 years. It means that for every store I have sales data and other features for 24 months.
I have to forecast sales for every store on a monthly basis. I have basic idea of LSTM but here its like 2000 time series with 145 features with just 24 data points or in other words for one time step, I have 2000 series with 145 features. what is the best approach to model so that I don't have to build model separately for each store.
