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 331–340 of 486
Which service is primarily used for batch processing in AWS?
A
AWS Lambda
B
AWS Glue
C
Amazon EC2
D
AWS Batch
AWS Batch is designed specifically for batch processing, while the others serve different purposes.
A data scientist needs to improve the accuracy of a model. What method should they apply?
A
Increase dataset size
B
Reduce model complexity
C
Use more features
D
Lower training epochs
Increasing dataset size typically leads to better model performance, whereas the other options may decrease accuracy.
You are configuring a machine learning model with Amazon SageMaker. What is the purpose of Hyperparameter Tuning?
A
Optimize model latency
B
Enhance data preprocessing
C
Improve model accuracy
D
Reduce training cost
Hyperparameter tuning aims to improve model accuracy by fine-tuning the parameters, while the other options are not its primary focus.
Which service is best for real-time data processing?
A
AWS Lambda
B
Amazon RDS
C
Amazon S3
D
AWS Glue
AWS Lambda allows real-time event-driven processing, whereas others focus on storage or batch processing.
A company needs to predict customer churn using historical data. Which machine learning service should they use?
A
Amazon SageMaker
B
Amazon Redshift
C
AWS Batch
D
AWS CloudFormation
Amazon SageMaker is designed for building, training, and deploying machine learning models.
What happens when you decrease the batch size in model training?
A
Faster training, less stable gradient
B
Slower training, more stable gradient
C
Increased overfitting risk
D
No impact on training
A smaller batch size leads to faster updates but can create noisy gradients, affecting stability.
Which service is used for deploying machine learning models on AWS?
A
Amazon SageMaker
B
AWS Lambda
C
Amazon EC2
D
Amazon RDS
Amazon SageMaker is specifically designed for model deployment, while the others serve different purposes.
A company needs to analyze real-time streaming data. Which service should they use?
A
Amazon S3
B
AWS Glue
C
Amazon Kinesis
D
AWS Batch
Amazon Kinesis is purpose-built for real-time data streaming, unlike the other services listed.
What happens when a model is overfitting?
A
High training accuracy, low validation accuracy
B
Balanced accuracy on both datasets
C
Simple model performs better
D
Reduced training epochs
Overfitting results in excellent training performance but poor generalization on unseen data.
Which service provides a fully managed ML model training platform?
A
Amazon SageMaker
B
AWS Lambda
C
Amazon Aurora
D
AWS CloudFormation
Amazon SageMaker is designed for ML model training, while others serve different purposes.