| CPC G06F 9/542 (2013.01) [G06N 20/00 (2019.01)] | 20 Claims |
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1. A method comprising:
processing event data with a preprocessing application to generate model input data and cardinality data of the model input data, wherein the model input data and cardinality data are generated in response to receiving the event data from a streaming application that received the event data from a source application and stores the event data using an event record corresponding to an event partition of an event topic;
forwarding, using the cardinality data of the model input data, the model input data to a machine learning model, wherein the cardinality data is processed using a cardinality threshold and wherein when the cardinality threshold is not met, the model input data are sent to and processed by a different machine learning model for model input data having low cardinality;
processing the model input data with the machine learning model to generate model output data stored to an output record corresponding to an output partition of an output topic of the streaming application;
processing the model output data from the output record with a post processing application to generate post data stored to a post record corresponding to a post partition of a post topic of the streaming application;
generating notification data using the post data of the post record; and
transmitting a notification of the notification data.
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