Abstract: At a network-accessible artificial intelligence service for time series predictions, a recurrent neural network model is trained using a plurality of time series of demand observations to generate demand forecasts for various items. A probabilistic demand forecast is generated for a target item using multiple executions of the trained model. Within the training set used for the model, the count of demand observations of the target item may differ from the count of demand observations of other items. A representation of the probabilistic demand forecast may be provided via a programmatic interface.