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MLS-C01 Reviews Questions

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Total 322 questions

AWS Certified Machine Learning - Specialty Questions and Answers

Question 17

An office security agency conducted a successful pilot using 100 cameras installed at key locations within the main office. Images from the cameras were uploaded to Amazon S3 and tagged using Amazon Rekognition, and the results were stored in Amazon ES. The agency is now looking to expand the pilot into a full production system using thousands of video cameras in its office locations globally. The goal is to identify activities performed by non-employees in real time.

Which solution should the agency consider?

Options:

A.

Use a proxy server at each local office and for each camera, and stream the RTSP feed to a uniqueAmazon Kinesis Video Streams video stream. On each stream, use Amazon Rekognition Video and createa stream processor to detect faces from a collection of known employees, and alert when non-employeesare detected.

B.

Use a proxy server at each local office and for each camera, and stream the RTSP feed to a uniqueAmazon Kinesis Video Streams video stream. On each stream, use Amazon Rekognition Image to detectfaces from a collection of known employees and alert when non-employees are detected.

C.

Install AWS DeepLens cameras and use the DeepLens_Kinesis_Video module to stream video toAmazon Kinesis Video Streams for each camera. On each stream, use Amazon Rekognition Video andcreate a stream processor to detect faces from a collection on each stream, and alert when nonemployeesare detected.

D.

Install AWS DeepLens cameras and use the DeepLens_Kinesis_Video module to stream video toAmazon Kinesis Video Streams for each camera. On each stream, run an AWS Lambda function tocapture image fragments and then call Amazon Rekognition Image to detect faces from a collection ofknown employees, and alert when non-employees are detected.

Question 18

A Machine Learning Specialist previously trained a logistic regression model using scikit-learn on a local

machine, and the Specialist now wants to deploy it to production for inference only.

What steps should be taken to ensure Amazon SageMaker can host a model that was trained locally?

Options:

A.

Build the Docker image with the inference code. Tag the Docker image with the registry hostname andupload it to Amazon ECR.

B.

Serialize the trained model so the format is compressed for deployment. Tag the Docker image with theregistry hostname and upload it to Amazon S3.

C.

Serialize the trained model so the format is compressed for deployment. Build the image and upload it toDocker Hub.

D.

Build the Docker image with the inference code. Configure Docker Hub and upload the image to Amazon ECR.

Question 19

A Machine Learning Specialist wants to determine the appropriate SageMaker Variant Invocations Per Instance setting for an endpoint automatic scaling configuration. The Specialist has performed a load test on a single instance and determined that peak requests per second (RPS) without service degradation is about 20 RPS As this is the first deployment, the Specialist intends to set the invocation safety factor to 0 5

Based on the stated parameters and given that the invocations per instance setting is measured on a per-minute basis, what should the Specialist set as the sageMaker variant invocations Per instance setting?

Options:

A.

10

B.

30

C.

600

D.

2,400

Question 20

A machine learning (ML) specialist needs to solve a binary classification problem for a marketing dataset. The ML specialist must maximize the Area Under the ROC Curve (AUC) of the algorithm by training an XGBoost algorithm. The ML specialist must find values for the eta, alpha, min_child_weight, and max_depth hyperparameter that will generate the most accurate model.  

Which approach will meet these requirements with the LEAST operational overhead?  

Options:

A.

Use a bootstrap script to install scikit-learn on an Amazon EMR cluster. Deploy the EMR cluster. Apply k-fold cross-validation methods to the algorithm.

B.

Deploy Amazon SageMaker prebuilt Docker images that have scikit-learn installed. Apply k-fold cross-validation methods to the algorithm.

C.

Use Amazon SageMaker automatic model tuning (AMT). Specify a range of values for each hyperparameter.

D.

Subscribe to an AUC algorithm that is on AWS Marketplace. Specify a range of values for each hyperparameter.

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Total 322 questions