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MLS-C01 - AWS Certified Machine Learning - Specialty

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MLS-C01 Questions and Answers

Question # 1

A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training. The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs.

What does the Specialist need to do?


Bundle the NVIDIA drivers with the Docker image.


Build the Docker container to be NVIDIA-Docker compatible.


Organize the Docker container's file structure to execute on GPU instances.


Set the GPU flag in the Amazon SageMaker CreateTrainingJob request body

Question # 2

A Machine Learning Specialist must build out a process to query a dataset on Amazon S3 using Amazon Athena The dataset contains more than 800.000 records stored as plaintext CSV files Each record contains 200 columns and is approximately 1 5 MB in size Most queries will span 5 to 10 columns only

How should the Machine Learning Specialist transform the dataset to minimize query runtime?


Convert the records to Apache Parquet format


Convert the records to JSON format


Convert the records to GZIP CSV format


Convert the records to XML format

Question # 3

A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket. A Machine Learning Specialist wants to use SQL to run queries on this data.

Which solution requires the LEAST effort to be able to query this data?


Use AWS Data Pipeline to transform the data and Amazon RDS to run queries.


Use AWS Glue to catalogue the data and Amazon Athena to run queries.


Use AWS Batch to run ETL on the data and Amazon Aurora to run the queries.


Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries.

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