Question 1

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 2

How does the Amazon flywheel model ensure continuous improvement and growth?

Options :

A : By using feedback loops that integrate customer experience, selection, and pricing.

B : By limiting the scope of operational improvements to cost reduction only.

C : By avoiding changes to business practices.

D : By maintaining a static approach to business operations.

Answer: A

Question 3

A manufacturing company wants to monitor its devices for anomalous behavior.A data scientist has trained an Amazon SageMaker scikit-learn model that classifies a device as normal or anomalous based on its 4-day telemetry.The 4-day telemetry of each device is collected in a separate file and is placed in an Amazon S3 bucket once every hour. The total time to run the model across the telemetry for all devices is 5 minutes.What is the MOST cost-effective solution for the company to use to run the model across the telemetry for all the devices?

Options :

A : SageMaker Processing

B : SageMaker Asynchronous Inference

C : SageMaker Batch Transform

D : A SageMaker multi-container endpoint

Answer: A

Question 4

What is an indication that ML might be an overcomplicated solution?

Options :

A : The problem involves generating personalized responses.

B : The problem can be solved with traditional algorithms.

C : The problem involves complex and dynamic data.

D : The problem requires quick adaptation to new data.

Answer: B

Question 5

Why is it important to estimate the amount of uncertainty in an ML model?

Options :

A : To improve the model-s computational efficiency

B : To increase the speed of data processing

C : To reduce the amount of training data needed

D : To avoid potential misinterpretations of life and property

Answer: D