Amazon Exam MLS-C01 Topic 3 Question 122 Discussion

Actual exam question for Amazon's MLS-C01 exam

Question #: 122
Topic #: 3

[Data Engineering]

A Machine Learning Specialist is preparing data for training on Amazon SageMaker The Specialist 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'?

AUse the SageMaker batch transform feature to transform the training data into a DataFrame

BUse AWS Glue to compress the data into the Apache Parquet format

CTransform the dataset into the Recordio protobuf format

DUse the SageMaker hyperparameter optimization feature to automatically optimize the data

Show Suggested Answer

Suggested Answer: C

by Gilberto at Oct 17, 2025, 01:13 PM

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Rodney

2 days ago

I'm a bit confused by this question. Does the Specialist need to compress the data or just transform it into a different format? I'm not sure if option B is the right approach here.

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Staci

8 days ago

I think I'd go with option C. Transforming the dataset into the Recordio protobuf format seems like the best way to optimize the data for training on SageMaker.

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Ashton

13 days ago

I recall that hyperparameter optimization is more about tuning the model rather than optimizing data. So, I don't think option D is the answer.

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France

19 days ago

I feel like we went over this in our study group. Using SageMaker's batch transform feature seems like it could be a good option, but I'm not confident.

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Vivan

24 days ago

I'm not entirely sure, but I think transforming the dataset into Recordio protobuf format might be the right choice. It sounds familiar from the practice questions.

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Celeste

1 month ago

I remember we discussed the importance of data formats in our last class. I think using Apache Parquet could really help with speed.

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