Question 1

Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?

Options :

A : Integration with Amazon S3 for object storage

B : Support for geospatial indexing and queries

C : Scalable index management and nearest neighbor search capability

D : Ability to perform real-time analysis on streaming data

Answer: C

Question 2

Which of the following services is specifically designed to provide insights into model predictions by explaining how input features contribute to the final output?

Options :

A : Amazon SageMaker Clarify

B : Amazon SageMaker Feature Store

C : Amazon SageMaker Model Monitor

D : Amazon SageMaker Canvas

Answer: A

Question 3

Which Amazon SageMaker service/tool offers a centralized view of all the Machine Learning models created in your AWS account?

Options :

A : Amazon SageMaker Ground Truth

B : Amazon SageMaker Model Dashboard

C : Amazon SageMaker Clarify

D : Amazon SageMaker Model Monitor

Answer: B

Question 4

What is the key difference between a training set, validation set, and test set in the context of machine learning?

Options :

A : The training set is used for tuning hyperparameters, the validation set is used for evaluating the final model performance, and the test set is used for training the model

B : The training set is used for training the model, the validation set is used for tuning hyperparameters and model selection, and the test set is used for evaluating the final model performance

C : The training set, validation set, and test set all serve the same purpose of evaluating the model performance

D : The training set is used for evaluating model performance, the validation set is used for training the model, and the test set is used for hyperparameter tuning

Answer: B

Question 5

Which of the following is correct regarding underfitting/overfitting in machine learning?

Options :

A : Underfit models experience low bias, whereas, overfit models experience high variance

B : Underfit models experience high bias, whereas, overfit models experience high variance

C : Underfit models experience low bias, whereas, overfit models experience low variance

D : Underfit models experience high bias, whereas, overfit models experience low variance

Answer: B