The art of machine learning operations in TensorFlow ecosystem
summary
Covers an end-to-end MLOps workflow inside the TensorFlow ecosystem: builds a reproducible TFX pipeline, wires CI/CD with Kubeflow Pipelines, and deploys models to TensorFlow Serving and TensorFlow Lite. Demonstrates automated data and model validation that catches three drift types, an example pipeline that cuts deployment time from days to hours, and a monitoring/rollback setup that proves the deployed model stays within measured SLA.
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