What feature engineering and model development approach should the Specialist take with a dataset this large?
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
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
D . Use Amazon ML for both feature engineering and model development.
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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