Question 1

What characterizes a simple machine learning model?

Options :

A : Low accuracy but high explainability

B : High accuracy and high explainability

C : Low accuracy and low explainability

D : High accuracy but low explainability

Answer: A

Question 2

A Machine Learning Specialist is preparing data for training on Amazon SageMaker.The Specialist is using one of the SageMaker built-in algorithms for the training.The dataset is stored in .CSV format and is transformed into a numpy.array, which appears to be negatively affecting the speed of the training.What should the Specialist do to optimize the data for training on SageMaker?

Options :

A : Use AWS Glue to compress the data into the Apache Parquet format.

B : Use the SageMaker hyperparameter optimization feature to automatically optimize the data.

C : Transform the dataset into the RecordIO protobuf format.

D : Use the SageMaker batch transform feature to transform the training data into a DataFrame.

Answer: C

Question 3

The 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?

Options :

A : Organize the Docker container-s file structure to execute on GPU instances.

B : Set the GPU flag in the Amazon SageMaker CreateTrainingJob request body.

C : Build the Docker container to be NVIDIA-Docker compatible.

D : Bundle the NVIDIA drivers with the Docker image.

Answer: D

Question 4

A company is using Amazon Textract to extract textual data from thousands of scanned text-heavy legal documents daily.The company uses this information to process loan applications automatically. Some of the documents fail business validation and are returned to human reviewers, who investigate the errors. This activity increases the time to process the loan applications.What should the company do to reduce the processing time of loan applications?

Options :

A : Use an Amazon Textract synchronous operation instead of an asynchronous operation.

B : Use Amazon Rekognition-s feature to detect text in an image to extract the data from scanned images. Use this information to process the loan applications.

C : Configure Amazon Textract to route low-confidence predictions to Amazon SageMaker Ground Truth. Perform a manual review on those words before performing a business validation.

D : Configure Amazon Textract to route low-confidence predictions to Amazon Augmented AI (Amazon A2I). Perform a manual review on those words before performing a business validation.

Answer: D

Question 5

What is the significance of predictions in Amazon's ML flywheel?

Options :

A : Predictions drive efficiency improvements and new capabilities.

B : Predictions have minimal impact on business practices.

C : Predictions are discarded after initial use.

D : Predictions are used to validate past performance.

Answer: A