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MLS-C01 · Question #233

A machine learning (ML) specialist has prepared and used a custom container image with Amazon SageMaker to train an image classification model. The ML specialist is performing hyperparameter optimizat

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Machine Learning Implementation and Operations

Question

A machine learning (ML) specialist has prepared and used a custom container image with Amazon SageMaker to train an image classification model. The ML specialist is performing hyperparameter optimization (HPO) with this custom container image to produce a higher quality image classifier. The ML specialist needs to determine whether HPO with the SageMaker built-in image classification algorithm will produce a better model than the model produced by HPO with the custom container image. All ML experiments and HPO jobs must be invoked from scripts inside SageMaker Studio notebooks. How can the ML specialist meet these requirements in the LEAST amount of time?

Options

  • APrepare a custom HPO script that runs multiple training jobs in SageMaker Studio in local mode
  • BUse SageMaker Autopilot to tune the model of the custom container image. Use the automatic
  • CUse SageMaker Experiments to run and manage multiple training jobs and tune the model of the
  • DUse the automatic model tuning capability of SageMaker to tune the models of the custom

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Topics

#SageMaker Experiments#Hyperparameter Optimization (HPO)#Model comparison#SageMaker Studio
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