Abstract: Systems and methods of time series modeling is provided. A system identifies a first dataset that includes a plurality of time series having a plurality of characteristics. A first time series of the plurality of time series can include one or more characteristics of the plurality of characteristics that are different from characteristics of a second time series of the plurality of time series. The system selects, based at least in part on the plurality of characteristics, a plurality of models. The system trains, via machine learning, the plurality of models with the first dataset. The system generates a model based at least in part on a combination of the plurality of models. The system deploys the model to output one or more predictions responsive to a second dataset. The second dataset can be different from the first dataset and can have at least one of the plurality of characteristics.