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Опубликовано 18 ноября 2021, 23:21
In this video, you’ll see how to automate machine learning operations (MLOps) with SageMaker projects. With this capability, you can enable faster model training and deployment, apply DevOps practices to the machine learning (ML) ecosystem, and standardize governance practices in ML projects.
Learn more:
SageMaker Projects - go.aws/3HM69tZ
SageMaker Project Templates - go.aws/3HM65KL
Machine Learning Blog - go.aws/3oKWVW3
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.
#AWS #AmazonWebServices #CloudComputing #AWSDemo
Learn more:
SageMaker Projects - go.aws/3HM69tZ
SageMaker Project Templates - go.aws/3HM65KL
Machine Learning Blog - go.aws/3oKWVW3
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.
#AWS #AmazonWebServices #CloudComputing #AWSDemo
Свежие видео
Enhance data access governance with enforced metadata rules in Amazon DataZone | Amazon Web Services