Exam AWS Certified Machine Learning - Specialty topic 1 question 56 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty

Question #: 56
Topic #: 1

[All AWS Certified Machine Learning - Specialty Questions]

A Machine Learning Specialist is preparing data for training on Amazon SageMaker. The Specialist is using one of the SageMaker built-in algorithms for the training. The dataset is stored in .CSV format and is transformed into a numpy.array, which appears to be negatively affecting the speed of the training.
What should the Specialist do to optimize the data for training on SageMaker?

A. Use the SageMaker batch transform feature to transform the training data into a DataFrame.
B. Use AWS Glue to compress the data into the Apache Parquet format.
C. Transform the dataset into the RecordIO protobuf format.
D. Use the SageMaker hyperparameter optimization feature to automatically optimize the data.

Show Suggested Answer

Suggested Answer: C 🗳️

by rsimham at Dec. 10, 2019, 3:28 a.m.

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rsimham

Highly Voted 2 years, 9 months ago

C is okay

upvoted 19 times

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stamarpadar

Highly Voted 2 years, 8 months ago

Anwer is C. Most Amazon SageMaker algorithms work best when you use the optimized protobuf recordIO format for the training data. https://docs.aws.amazon.com/sagemaker/latest/dg/cdf-training.html

upvoted 16 times

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Mickey321

Most Recent 10 months ago

Selected Answer: C

option C

upvoted 1 times

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AjoseO

1 year, 4 months ago

Selected Answer: C

The Specialist should transform the dataset into the RecordIO protobuf format. This format is optimized for use with SageMaker and has been shown to improve the speed and efficiency of training algorithms. Using the RecordIO protobuf format is a best practice for preparing data for use with Amazon SageMaker, and it is specifically recommended for use with the built-in algorithms.

upvoted 1 times

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