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Exam AWS Certified Machine Learning - Specialty All Questions

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Exam AWS Certified Machine Learning - Specialty topic 1 question 252 discussion

A manufacturing company wants to create a machine learning (ML) model to predict when equipment is likely to fail. A data science team already constructed a deep learning model by using TensorFlow and a custom Python script in a local environment. The company wants to use Amazon SageMaker to train the model.

Which TensorFlow estimator configuration will train the model MOST cost-effectively?

  • A. Turn on SageMaker Training Compiler by adding compiler_config=TrainingCompilerConfig() as a parameter. Pass the script to the estimator in the call to the TensorFlow fit() method.
  • B. Turn on SageMaker Training Compiler by adding compiler_config=TrainingCompilerConfig() as a parameter. Turn on managed spot training by setting the use_spot_instances parameter to True. Pass the script to the estimator in the call to the TensorFlow fit() method.
  • C. Adjust the training script to use distributed data parallelism. Specify appropriate values for the distribution parameter. Pass the script to the estimator in the call to the TensorFlow fit() method.
  • D. Turn on SageMaker Training Compiler by adding compiler_config=TrainingCompilerConfig() as a parameter. Set the MaxWaitTimeInSeconds parameter to be equal to the MaxRuntimeInSeconds parameter. Pass the script to the estimator in the call to the TensorFlow fit() method.
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Suggested Answer: B 🗳️

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loict
Highly Voted 7 months, 1 week ago
Selected Answer: B
A. NO - should use Spot instances B. YES - makes use of compiler and spot instances C. NO - that is to minimize training time, not reduced cost D. NO - MaxWaitTimeInSeconds is time to find a free spot instance, it is unrelated to MaxRuntimeInSeconds which is processing time once an istance has been acquired
upvoted 5 times
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Mickey321
Most Recent 8 months ago
Selected Answer: B
managed spot
upvoted 1 times
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brianb08
9 months, 4 weeks ago
Selected Answer: B
B is the only option which mentions spot instances... the question is to be most cost effective, so seems B is only viable option.
upvoted 4 times
kaike_reis
8 months, 1 week ago
I go with you
upvoted 1 times
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Mickey321
10 months, 2 weeks ago
Selected Answer: B
B. Turn on SageMaker Training Compiler by adding compiler_config=TrainingCompilerConfig() as a parameter. Turn on managed spot training by setting the use_spot_instances parameter to True. Pass the script to the estimator in the call to the TensorFlow fit() method.
upvoted 2 times
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