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MLS-C01 · Question #223

A geospatial analysis company processes thousands of new satellite images each day to produce vessel detection data for commercial shipping. The company stores the training data in Amazon S3. The…

The correct answer is B. Modify the training configuration to use Pipe input mode. https://aws.amazon.com/blogs/machine-learning/using-pipe-input-mode-for-amazon-sagemaker-

Machine Learning Implementation and Operations

Question

A geospatial analysis company processes thousands of new satellite images each day to produce vessel detection data for commercial shipping. The company stores the training data in Amazon S3. The training data incrementally increases in size with new images each day. The company has configured an Amazon SageMaker training job to use a single ml.p2.xlarge instance with File input mode to train the built-in Object Detection algorithm. The training process was successful last month but is now failing because of a lack of storage. Aside from the addition of training data, nothing has changed in the model training process. A machine learning (ML) specialist needs to change the training configuration to fix the problem. The solution must optimize performance and must minimize the cost of training. Which solution will meet these requirements?

Options

  • AModify the training configuration to use two ml.p2.xlarge instances.
  • BModify the training configuration to use Pipe input mode.
  • CModify the training configuration to use a single ml.p3.2xlarge instance.
  • DModify the training configuration to use Amazon Elastic File System (Amazon EFS) instead of

How the community answered

(26 responses)
  • A
    4% (1)
  • B
    81% (21)
  • C
    12% (3)
  • D
    4% (1)

Explanation

https://aws.amazon.com/blogs/machine-learning/using-pipe-input-mode-for-amazon-sagemaker-

Topics

#SageMaker Training#Data Input Modes#Cost Optimization#Storage Management

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