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MLS-C01 · Question #310

MLS-C01 Question #310: Real Exam Question with Answer & Explanation

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Machine Learning Implementation and Operations

Question

A mining company wants to use machine learning (ML) models to identify mineral images in real time. A data science team built an image recognition model that is based on convolutional neural network (CNN). The team trained the model on Amazon SageMaker by using GPU instances. The team will deploy the model to a SageMaker endpoint. The data science team already knows the workload traffic patterns. The team must determine instance type and configuration for the workloads. Which solution will meet these requirements with the LEAST development effort?

Options

  • ARegister the model artifact and container to the SageMaker Model Registry. Use the SageMaker
  • BRegister the model artifact and container to the SageMaker Model Registry. Use the SageMaker
  • CDeploy the model to an endpoint by using GPU instances. Use AWS Lambda and Amazon API
  • DDeploy the model to an endpoint by using CPU instances. Use AWS Lambda and Amazon API

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Topics

#SageMaker Inference Recommender#Model Deployment#MLOps#Resource Optimization
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