You got a lot of time series and want to predict the next step (or steps). What should you do now? Train a model for each series? Is there a way to fit a model for all the series together? Which is better?
I have seen many data scientists think about approaching this problem by creating a single model for each product. Although this is one of the possible solutions, it’s not likely to be the best.
Here I will demonstrate how to train a single model to predict multiple time series at the same time. This technique usually creates powerful models that help teams win machine learning competitions and can be used in your project.