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AWS Updates Edge Vision Pipeline Pattern Using SageMaker SDK v3
AWS updated its edge computer vision MLOps pattern using Amazon SageMaker Python SDK v3, replacing SageMaker Edge Manager with SageMaker Neo to automate per-camera training and edge compilation.
AWS published an updated MLOps pipeline sample using SageMaker Python SDK v3 to manage edge computer vision fleets. The sample architecture deploys a dual-branch SageMaker Pipeline that trains an anomaly detector and a defect classifier per camera. Models undergo ONNX evaluation against quality gates before automated compilation with SageMaker Neo and registration in the SageMaker Model Registry.
Key takeaways
- The pipeline updates edge MLOps patterns for SageMaker SDK v3, replacing deprecated SageMaker Edge Manager with SageMaker Neo.
- Each camera branch trains an autoencoder and classifier, validating ONNX exports before compiling artifacts for edge targets.
Source：AWS Machine Learning Read the original ↗
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