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Training and Deployment of H2O Models with Amazon SageMaker
by David Turner
on 30 OCT 2020
in Amazon Corretto, Amazon SageMaker, Application Services, Artificial Intelligence, Auto Scaling, AWS Serverless Application Model, AWS Step Functions, AWS Systems Manager, Containers, Java, Management Tools
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The processes of model training and deployment are critical elements of a comprehensive machine learning (ML) pipeline. Each of these phases often necessitates distinct software and hardware configurations to achieve optimal results in a production setting. Model training focuses on minimizing costs, ensuring a practical overall run time, enhancing scientific adaptability, and achieving model interpretability. Conversely, the deployment stage emphasizes efficiency and scalability.
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