Amazon Web Services783 тыс
Опубликовано 18 апреля 2023, 21:32
Amazon SageMaker shadow testing enables you to evaluate a new ML model prior to deploying it in production by comparing its performance against the model already in production. Testing models before production deployment can help you catch potential configuration errors and performance issues and prevent negative end user experience. In this video, learn more about how you can run shadow testing using Amazon SageMaker.
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ABOUT AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers — including the fastest-growing startups, largest enterprises, and leading government agencies — are using AWS to lower costs, become more agile, and innovate faster.
#machinelearning #SageMaker #SageMakershadowtesting #SageMakermodeldeployment #SageMakerInference #AWS #AmazonWebServices #CloudComputing
Learn more at: go.aws/3o7NEe0
Subscribe:
More AWS videos go.aws/3m5yEMW
More AWS events videos: go.aws/3ZHq4BK
Do you have technical AWS questions?
Ask the community of experts on AWS re:Post: go.aws/3lPaoPb
ABOUT AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers — including the fastest-growing startups, largest enterprises, and leading government agencies — are using AWS to lower costs, become more agile, and innovate faster.
#machinelearning #SageMaker #SageMakershadowtesting #SageMakermodeldeployment #SageMakerInference #AWS #AmazonWebServices #CloudComputing
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