Slightly of topic but maybe someone have a good answer 😊 I am in the process of making a ML model for the next 24 hours each day. What is the best way to make this? A single model with hour as a cyclic feature (a lot easier to maintain since it is only a single model) or make 24 individual models, one for each hour? I am currently using xgboost and lightgbm

Using the MLForecast library, you can just define the

freq

. And then you can just do:

model.predict(24)

to predict the next 24 hours. It can be one model, and probably should be. See this

Thanks I Will look into it 😊