Free AWS-Certified-Machine-Learning-Specialty Exam Braindumps

IT leadership wants Jo transition a company's existing machine learning data storage environment to AWS as a temporary ad hoc solution The company currently uses a custom software process that heavily leverages SOL as a query language and exclusively stores generated csv documents for machine learning
The ideal state for the company would be a solution that allows it to continue to use the current workforce of SQL experts The solution must also support the storage of csv and JSON files, and be able to query over semi-structured data The following are high priorities for the company:
• Solution simplicity
• Fast development time
• Low cost
• High flexibility
What technologies meet the company's requirements?

1. A. Amazon S3 and Amazon Athena
2. B. Amazon Redshift and AWS Glue
3. C. Amazon DynamoDB and DynamoDB Accelerator (DAX)
4. D. Amazon RDS and Amazon ES

Correct Answer: B

An e-commerce company needs a customized training model to classify images of its shirts and pants products The company needs a proof of concept in 2 to 3 days with good accuracy Which compute choice should the Machine Learning Specialist select to train and achieve good accuracy on the model quickly?

1. A. m5 4xlarge (general purpose)
2. B. r5.2xlarge (memory optimized)
3. C. p3.2xlarge (GPU accelerated computing)
4. D. p3 8xlarge (GPU accelerated computing)

Correct Answer: C

A machine learning (ML) specialist is administering a production Amazon SageMaker endpoint with model monitoring configured. Amazon SageMaker Model Monitor detects violations on the SageMaker endpoint, so the ML specialist retrains the model with the latest dataset. This dataset is statistically representative of the current production traffic. The ML specialist notices that even after deploying the new SageMaker model and running the first monitoring job, the SageMaker endpoint still has violations.
What should the ML specialist do to resolve the violations?

1. A. Manually trigger the monitoring job to re-evaluate the SageMaker endpoint traffic sample.
2. B. Run the Model Monitor baseline job again on the new training se
3. C. Configure Model Monitor to use the new baseline.
4. D. Delete the endpoint and recreate it with the original configuration.
5. E. Retrain the model again by using a combination of the original training set and the new training set.

Correct Answer: B

A Machine Learning Specialist is developing recommendation engine for a photography blog Given a picture, the recommendation engine should show a picture that captures similar objects The Specialist would like to create a numerical representation feature to perform nearest-neighbor searches
What actions would allow the Specialist to get relevant numerical representations?

1. A. Reduce image resolution and use reduced resolution pixel values as features
2. B. Use Amazon Mechanical Turk to label image content and create a one-hot representation indicating the presence of specific labels
3. C. Run images through a neural network pie-trained on ImageNet, and collect the feature vectors from the penultimate layer
4. D. Average colors by channel to obtain three-dimensional representations of images.

Correct Answer: A

A company will use Amazon SageMaker to train and host a machine learning (ML) model for a marketing campaign. The majority of data is sensitive customer data. The data must be encrypted at rest. The company wants AWS to maintain the root of trust for the master keys and wants encryption key usage to be logged.
Which implementation will meet these requirements?

1. A. Use encryption keys that are stored in AWS Cloud HSM to encrypt the ML data volumes, and to encryptthe model artifacts and data in Amazon S3.
2. B. Use SageMaker built-in transient keys to encrypt the ML data volume
3. C. Enable default encryption for new Amazon Elastic Block Store (Amazon EBS) volumes.
4. D. Use customer managed keys in AWS Key Management Service (AWS KMS) to encrypt the ML data volumes, and to encrypt the model artifacts and data in Amazon S3.
5. E. Use AWS Security Token Service (AWS STS) to create temporary tokens to encrypt the ML storage volumes, and to encrypt the model artifacts and data in Amazon S3.

Correct Answer: C