AWS Machine Learning Blog· WonGu Rho·· 2 d ago
Production MLOps at GS Caltex with Amazon SageMaker Canvas, part 1
Production MLOps at GS Caltex with Amazon SageMaker Canvas, part 1
AI summary
GS Caltex connects Amazon SageMaker Canvas to Amazon SageMaker Pipelines so process engineers' no-code models run in production. This post shows how ML engineers reuse validated preprocessing flows and models, cutting deployment from about a week to a few hours and running batch inference every 30 minutes.
Selection record
Threshold 60Official, first-handFirst 22Second 22
Not admittedSum of both 44 < twice the threshold 120
- Source tier
- Official, first-hand; this tier's threshold is 60
- Pre-filter
- passed：SageMaker Canvas与Pipelines的MLOps生产实践
A model scores each item twice, independently, against one written standard, out of 100. An item is admitted only when the two scores add up to twice the threshold. The threshold is set per source tier.
Source: AWS Machine Learning Blog · aws.amazon.com