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Effectively solve distributed training convergence issues with Amazon SageMaker Hyperband Automatic Model Tuning

AWS Machine Learning Blog

JULY 13, 2023

Recent years have shown amazing growth in deep learning neural networks (DNNs). Amazon SageMaker distributed training jobs enable you with one click (or one API call) to set up a distributed compute cluster, train a model, save the result to Amazon Simple Storage Service (Amazon S3), and shut down the cluster when complete.

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Model hosting patterns in Amazon SageMaker, Part 1: Common design patterns for building ML applications on Amazon SageMaker

AWS Machine Learning Blog

JANUARY 9, 2023

This includes loading the model from Amazon Simple Storage Service (Amazon S3), for example, database lookups to validate the input, obtaining pre-computed features from the feature store, and so on. The infrastructure costs are the combined costs for storage, network, and compute. Throughput (transactions per second).

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Artificial Intelligence Zone

Effectively solve distributed training convergence issues with Amazon SageMaker Hyperband Automatic Model Tuning

Model hosting patterns in Amazon SageMaker, Part 1: Common design patterns for building ML applications on Amazon SageMaker

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