How Seldon Helps You Understand Your Deployed Model Usage
Production machine learning deployment is increasingly multi-faceted. Mission-critical systems often demand redundancy, high throughput or low latency, all of which can mean deploying a model multiple times across many pieces of hardware. A traditional machine learning container-based usage count does not map well to the number of inference services being run. It also creates a […]
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