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Question 67 - MLS-C01 discussion

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A Machine Learning Specialist is working with multiple data sources containing billions of records that need to be joined. What feature engineering and model development approach should the Specialist take with a dataset this large?

A.
Use an Amazon SageMaker notebook for both feature engineering and model development
Answers
A.
Use an Amazon SageMaker notebook for both feature engineering and model development
B.
Use an Amazon SageMaker notebook for feature engineering and Amazon ML for model development
Answers
B.
Use an Amazon SageMaker notebook for feature engineering and Amazon ML for model development
C.
Use Amazon EMR for feature engineering and Amazon SageMaker SDK for model development
Answers
C.
Use Amazon EMR for feature engineering and Amazon SageMaker SDK for model development
D.
Use Amazon ML for both feature engineering and model development.
Answers
D.
Use Amazon ML for both feature engineering and model development.
Suggested answer: C

Explanation:

Amazon EMR is a service that can process large amounts of data efficiently and cost-effectively. It can run distributed frameworks such as Apache Spark, which can perform feature engineering on big data. Amazon SageMaker SDK is a Python library that can interact with Amazon SageMaker service to train and deploy machine learning models. It can also use Amazon EMR as a data source for training data.References:

Amazon EMR

Amazon SageMaker SDK

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asked 16/09/2024
Suraj Porwal
36 questions
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