An approach to model operationalization that uses real-time data in order to make model predictions rather than batch mode processing. Like real-time predictions, stream predictions make rapid, individual predictions on data as quickly as it is received, but stream learning predictions might be used further downstream by other systems rather than provide a result back to a user. Stream learning is also an alternative to the use of Microservices for on-demand access since the predictions can be made as part of another operation or activity on the server without making additional calls.
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