Amazon AWS
AWS Certified Machine Learning Engineer – Associate
MLA-C01
The AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam validates your skills in building, training, and deploying machine learning models on AWS. It is ideal for those looking to specialize in machine learning.
Questions 11–20 of 486
A company needs to process streaming data. Which service should they choose?
A
Amazon Kinesis
B
AWS Lambda
C
Amazon EC2
D
Amazon RDS
Amazon Kinesis is specifically designed for streaming data processing, while the others handle different workloads.
You are configuring a machine learning model. What happens if you choose too many features?
A
Overfitting may occur
B
Model accuracy increases
C
Training is faster
D
Cross-validation errors decrease
Too many features may lead to overfitting, which negatively impacts generalization.
Which service provides scalable object storage for data?
A
Amazon S3
B
AWS Lambda
C
Amazon RDS
D
Amazon EC2
Amazon S3 is designed for scalable object storage, while the others serve different purposes.
A company needs to automate machine learning model training. Which AWS service should they use?
A
AWS CodePipeline
B
Amazon SageMaker
C
AWS CloudFormation
D
Amazon EC2
Amazon SageMaker facilitates automated model training, while the others focus on different aspects of the AWS ecosystem.
What happens when you deploy an inference endpoint in Amazon SageMaker?
A
Model training starts automatically
B
Model predictions become available
C
Data is stored in S3
D
Permissions are granted to all users
Deploying an endpoint makes model predictions available, while the other options are not automatic outcomes of deployment.
Which service provides a fully managed environment for building ML models?
A
Amazon SageMaker
B
AWS Glue
C
Amazon RDS
D
AWS Lambda
Amazon SageMaker is designed specifically for machine learning.
A company needs to implement real-time data analysis on streaming data. Which AWS service should they use?
A
Amazon Redshift
B
AWS Glue
C
Amazon Kinesis
D
Amazon S3
Amazon Kinesis is ideal for real-time data streams.
You are configuring a Machine Learning model in SageMaker. What happens if you select a random seed of 0?
A
It guarantees unique model outputs
B
It allows reproducible results
C
It initializes parameters randomly
D
It mandates specific algorithm use
Choosing a random seed ensures results can be reproduced.
Which service is best for deploying machine learning models at scale on AWS?
A
Amazon SageMaker
B
AWS Lambda
C
Amazon EC2
D
AWS Glue
Amazon SageMaker is specifically designed for building, training, and deploying ML models, while others serve different purposes.
A company needs to process real-time streaming data for machine learning. Which service should they choose?
A
Amazon S3
B
Amazon Kinesis
C
AWS Batch
D
Amazon CloudWatch
Amazon Kinesis is designed for real-time data streaming, unlike the other options.