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Total 254 Questions | Updated On: Nov 18, 2024

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Question 1

A company is building a new version of a recommendation engine.Machine learning (ML) specialists need to keep adding new data from users to improve personalized recommendations.The ML specialists gather data from the users' interactions on the platform and from sources such as external websites and social media.The pipeline cleans, transforms, enriches, and compresses terabytes of data daily, and this data is stored in Amazon S3.A set of Python scripts was coded to do the job and is stored in a large Amazon EC2 instance.The whole process takes more than 20 hours to finish, with each script taking at least an hour.The company wants to move the scripts out of Amazon EC2 into a more managed solution that will eliminate the need to maintain servers.Which approach will address all of these requirements with the LEAST development effort?

A : Create a set of individual AWS Lambda functions to execute each of the scripts. Build a step function by using the AWS Step Functions Data Science SDK. Store the results in Amazon S3.

B : Create an AWS Glue job. Convert the scripts to PySpark. Execute the pipeline. Store the results in Amazon S3.

C : Load the data into Amazon DynamoDB. Convert the scripts to an AWS Lambda function. Execute the pipeline by triggering Lambda executions. Store the results in Amazon S3.

D : Load the data into an Amazon Redshift cluster. Execute the pipeline by using SQL. Store the results in Amazon S3.

Answer: C

Question 2

In what scenario would traditional programming techniques be preferable over ML?

A : When complex logic and scalability are required.

B : When the problem can be solved with simple rules.

C : When personalized recommendations are needed.

D : When quick adaptation to new data is necessary.

Answer: B

Question 3

How is deep learning different from general machine learning?

A : It requires no domain knowledge.

B : It uses a layered architecture mimicking the human brain.

C : It relies solely on historical data.

D : It is unrelated to pattern recognition.

Answer: B

Question 4

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?

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 5

What is the main goal of testing the model in ML?

A : To prepare the data for training

B : To generate predictions for new data

C : To construct input representations from raw variables

D : To evaluate the quality of the model on held-out data

Answer: D

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Total 254 Questions | Updated On: Nov 18, 2024

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