I have a dataset with sales numbers for ~500 different markets (assume different cities or regions) and need monthly forecasts for each market. Instead of building 500 different models, I'm interested in just training a single model with a single set of params to prevent me from having to manually feature engineer each market.
Can someone point me to some resources for this problem? I went through the similar Stack questions and they weren't as helpful for this particularly.
Specifically, I know that LSTMs are sometimes used here, but would classical approaches be effective as well?