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Exam Code: AWS-Certified-Machine-Learning-Specialty
Exam Title: AWS Certified Machine Learning - Specialty
Vendor: Amazon
Exam Questions: 208
Last Updated: December 18th,2024

Question 1

A Machine Learning Specialist is working with multiple data sources containing billions of records that need to be joined. What feature engineering and model development approach should the Specialist take with a dataset this large?

A. Use an Amazon SageMaker notebook for both feature engineering and model development
B. Use an Amazon SageMaker notebook for feature engineering and Amazon ML for model development
C. Use Amazon EMR for feature engineering and Amazon SageMaker SDK for model development
D. Use Amazon ML for both feature engineering and model development.

Correct Answer:B

Question 2

An online reseller has a large, multi-column dataset with one column missing 30% of its data A Machine Learning Specialist believes that certain columns in the dataset could be used to reconstruct the missing data.
Which reconstruction approach should the Specialist use to preserve the integrity of the dataset?

A. Listwise deletion
B. Last observation carried forward
C. Multiple imputation
D. Mean substitution

Correct Answer:C

Question 3

A machine learning specialist stores IoT soil sensor data in Amazon DynamoDB table and stores weather event data as JSON files in Amazon S3. The dataset in DynamoDB is 10 GB in size and the dataset in Amazon S3 is 5 GB in size. The specialist wants to train a model on this data to help predict soil moisture levels as a function of weather events using Amazon SageMaker.
Which solution will accomplish the necessary transformation to train the Amazon SageMaker model with the LEAST amount of administrative overhead?

A. Launch an Amazon EMR cluste
B. Create an Apache Hive external table for the DynamoDB table and S3 dat
C. Join the Hive tables and write the results out to Amazon S3.
D. Crawl the data using AWS Glue crawler
E. Write an AWS Glue ETL job that merges the two tables and writes the output to an Amazon Redshift cluster.
F. Enable Amazon DynamoDB Streams on the sensor tabl
G. Write an AWS Lambda function that consumes the stream and appends the results to the existing weather files in Amazon S3.
H. Crawl the data using AWS Glue crawler
I. Write an AWS Glue ETL job that merges the two tables and writes the output in CSV format to Amazon S3.

Correct Answer:C

Question 4

A company that runs an online library is implementing a chatbot using Amazon Lex to provide book recommendations based on category. This intent is fulfilled by an AWS Lambda function that queries an Amazon DynamoDB table for a list of book titles, given a particular category. For testing, there are only three categories implemented as the custom slot types: "comedy," "adventure,” and "documentary.”
A machine learning (ML) specialist notices that sometimes the request cannot be fulfilled because Amazon Lex cannot understand the category spoken by users with utterances such as "funny," "fun," and "humor." The ML specialist needs to fix the problem without changing the Lambda code or data in DynamoDB.
How should the ML specialist fix the problem?

A. Add the unrecognized words in the enumeration values list as new values in the slot type.
B. Create a new custom slot type, add the unrecognized words to this slot type as enumeration values, and use this slot type for the slot.
C. Use the AMAZON.SearchQuery built-in slot types for custom searches in the database.
D. Add the unrecognized words as synonyms in the custom slot type.

Correct Answer:C

Question 5

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?

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.
B. Use SageMaker built-in transient keys to encrypt the ML data volume
C. Enable default encryption for new Amazon Elastic Block Store (Amazon EBS) volumes.
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.
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