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Machine learning models in event-driven architectures

A variety of real-world processes produce sequences of data whose complex temporal dynamics need to be modeled. For example, real-time event-driven customer interaction systems capture user actions (events) generated by customers on web and mobile applications. These user actions across various digital end-points are directed towards achieving specific outcomes and represent certain user intent. The […]

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