MLS-C01 (Page 22)

A company is setting up an Amazon SageMaker environment.The corporate data security policy does not allow communication over the internet.How can the company enable the Amazon SageMaker service without enabling direct internet access to Amazon SageMaker notebook instances?Read More →

A Data Scientist needs to create a serverless ingestion and analytics solution for high-velocity, real-time streaming data.The ingestion process must buffer and convert incoming records from JSON to a query-optimized, columnar format without data loss.The output datastore must be highly available, and Analysts must be able to run SQL queries against the data and connect to existing business intelligence dashboards.Which solution should the Data Scientist build to satisfy the requirements?Read More →

A Machine Learning Specialist wants to bring a custom algorithm to Amazon SageMaker.The Specialist implements the algorithm in a Docker container supported by Amazon SageMaker.How should the Specialist package the Docker container so that Amazon SageMaker can launch the training correctly?Read More →

A Machine Learning Specialist trained a regression model, but the first iteration needs optimizing.The Specialist needs to understand whether the model is more frequently overestimating or underestimating the target.What option can the Specialist use to determine whether it is overestimating or underestimating the target value?Read More →

A company offers an online shopping service to its customers.The company wants to enhance the site’s security by requesting additional information when customers access the site from locations that are different from their normal location.The company wants to update the process to call a machine learning (ML) model to determine when additional information should be requested.The company has several terabytes of data from its existing ecommerce web servers containing the source IP addresses for each request made to the web server.For authenticated requests, the records also contain the login name of the requesting user.Which approach should an ML specialist take to implement the new security feature in the web application?Read More →

A company is observing low accuracy while training on the default built-in image classification algorithm in Amazon SageMaker.The Data Science team wants to use an Inception neural network architecture instead of a ResNet architecture.Which of the following will accomplish this? (Choose two.)Read More →

A manufacturing company uses machine learning (ML) models to detect quality issues.The models use images that are taken of the company’s product at the end of each production step.The company has thousands of machines at the production site that generate one image per second on average.The company ran a successful pilot with a single manufacturing machine.For the pilot, ML specialists used an industrial PC that ran AWS IoT Greengrass with a long-running AWS Lambda function that uploaded the images to Amazon S3.The uploaded images invoked a Lambda function that was written in Python to perform inference by using an Amazon SageMaker endpoint that ran a custom model.The inference results were forwarded back to a web service that was hosted at the production site to prevent faulty products from being shipped.The company scaled the solution out to all manufacturing machines by installing similarly configured industrial PCs on each production machine.However, latency for predictions increased beyond acceptable limits.Analysis shows that the internet connection is at its capacity limit.How can the company resolve this issue MOST cost-effectively?Read More →

An online store is predicting future book sales by using a linear regression model that is based on past sales data.The data includes duration, a numerical feature that represents the number of days that a book has been listed in the online store.A data scientist performs an exploratory data analysis and discovers that the relationship between book sales and duration is skewed and non-linear.Which data transformation step should the data scientist take to improve the predictions of the model?Read More →

A company maintains a 2 TB dataset that contains information about customer behaviors.The company stores the dataset in Amazon S3.The company stores a trained model container in Amazon Elastic Container Registry (Amazon ECR).A machine learning (ML) specialist needs to score a batch model for the dataset to predict customer behavior.The ML specialist must select a scalable approach to score the model.Which solution will meet these requirements MOST cost-effectively?Read More →

An ecommerce company wants to update a production real-time machine learning (ML) recommendation engine API that uses Amazon SageMaker.The company wants to release a new model but does not want to make changes to applications that rely on the API.The company also wants to evaluate the performance of the new model in production traffic before the company fully rolls out the new model to all users.Which solution will meet these requirements with the LEAST operational overhead?Read More →