AWS Certified AI Practitioner AIF-C01 Practice Question
A hospital needs an ML solution that analyzes patient vital signs continuously and triggers alerts within one second when anomalies occur. Which inferencing approach is most appropriate?
Batch inference that runs once each hour on accumulated data
Offline model training jobs executed nightly
Batch inference performed daily on archived patient records
Real-time (online) inference with a low-latency endpoint
Real-time (online) inference is designed for use cases that require very low-latency predictions as data arrives, such as monitoring patient vitals and issuing immediate alerts. Batch inference processes records in groups on a set schedule, so hourly or daily jobs would introduce unacceptable delays. Offline training produces or updates a model but does not deliver predictions to end users in real time, so it also fails to meet the one-second requirement.
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AWS Certified AI Practitioner AIF-C01
Fundamentals of AI and ML
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