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 481–486 of 486
Which AWS service is best for real-time data streaming?
A
Amazon Kinesis
B
Amazon S3
C
AWS Lambda
D
Amazon RDS
Amazon Kinesis is designed for real-time data streaming, while the others serve different purposes.
A company needs to predict customer churn using historical data. What type of ML model should they use?
A
Classification model
B
Regression model
C
Clustering model
D
Time-series model
A classification model is best for predicting categorical outcomes like churn.
You are configuring an Amazon SageMaker training job. What happens when you set the instance count to zero?
A
Job does not start
B
Job runs on minimum instances
C
Job starts but is idle
D
Job fails with an error
Setting instance count to zero means no instances are allocated, so the job cannot start.
Which AWS service is best for real-time data analytics?
A
Amazon Kinesis
B
AWS S3
C
Amazon RDS
D
AWS IoT Core
Amazon Kinesis is designed for real-time processing, while the others focus on storage or specific use cases.
A company needs to deploy a model that requires GPU support. Which service should they choose?
A
AWS SageMaker
B
AWS Lambda
C
Amazon EC2 Spot Instances
D
Amazon Elastic Beanstalk
AWS SageMaker provides integrated GPU support specifically for ML models, unlike Lambda and Beanstalk.
What happens when you use an overly complex model on limited training data?
A
Underfitting occurs
B
Model generalizes better
C
Overfitting occurs
D
Training speed increases significantly
Using a complex model on limited data typically leads to overfitting, fitting noise rather than the underlying pattern.