I have an application that receives ~10k of requests per day; each request has multiple parameters and goes through a pipeline with multiple steps and they finish in about 1 hour.
Let's say the requests are like
bake_cake [flavor=chocolate] [topping1=strawberry] [topping2=cream]
Given a history of requests from previous days, is there a ML framework that can help me predict the "100 most like requests to arrive today" so I can cache their results? Or some other similar strategy that can help me delivering part of those requests faster?
Ideally it would be based on how much I gain by delivering faster, how much I lose by processing a request that might not come, etc.; but for now even simpler algorithms could be of much help since currently there's no optimization.