Amazon Web Services782 тыс
Опубликовано 24 июня 2022, 15:29
Building an ML application involves developing models, data pipelines, training pipelines, inference pipelines, and validation tests. With the Amazon SageMaker Model Registry, you can track model versions, their metadata such as use case grouping, and model performance metrics baselines in a central repository where it is easy to choose the right model for deployment based on your business requirements. Model Registry automatically logs the approval workflows for audit and compliance.
Learn more: go.aws/3brnqg0
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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 #AWS #AmazonWebServices #CloudComputing
Learn more: go.aws/3brnqg0
Subscribe:
More AWS videos - bit.ly/2O3zS75
More AWS events videos - bit.ly/316g9t4
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 #AWS #AmazonWebServices #CloudComputing
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