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Typo fixed. rh-aiservices-bu#99
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@DanielFroehlich
DanielFroehlich committed Aug 30, 2021
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This “AI/ML Industrial Edge” demo shows how condition based monitoring can be implemented using AI/ML. Machine inference-based anomaly detection on metric time-series sensor data at the edge, with a central data lake and ML model retraining. It also shows how hybrid deployments (cluster at the edge and in the cloud) can be managed, and how the CI/CD pipelines and Model Training/Execution flows can be implemented.

This demon is using OpenShift, ACM, AMQ Streams, OpenDataHub, and other products from Red Hat’s portfolio
This demo is using OpenShift, ACM, AMQ Streams, OpenDataHub, and other products from Red Hat’s portfolio

This is the frontend at the factory:

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