Machine Learning Specialty (Page 25)

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 →

A data scientist is designing a repository that will contain many images of vehicles.The repository must scale automatically in size to store new images every day.The repository must support versioning of the images.The data scientist must implement a solution that maintains multiple immediately accessible copies of the data in different AWS Regions.Which solution will meet these requirements?Read More →

A company sells thousands of products on a public website and wants to automatically identify products with potential durability problems.The company has1.000 reviews with date, star rating, review text, review summary, and customer email fields, but many reviews are incomplete and have empty fields.Each review has already been labeled with the correct durability result.A machine learning specialist must train a model to identify reviews expressing concerns over product durability.The first model needs to be trained and ready to review in 2 days.What is the MOST direct approach to solve this problem within 2 days?Read More →

A data scientist has a dataset of machine part images stored in Amazon Elastic File System (Amazon EFS).The data scientist needs to use Amazon SageMaker to create and train an image classification machine learning model based on this dataset.Because of budget and time constraints, management wants the data scientist to create and train a model with the least number of steps and integration work required.How should the data scientist meet these requirements?Read More →

A music streaming company is building a pipeline to extract features.The company wants to store the features for offline model training and online inference.The company wants to track feature history and to give the company’s data science teams access to the features.Which solution will meet these requirements with the MOST operational efficiency?Read More →

A global company receives and processes hundreds of documents daily.The documents are in printed .pdf format or .jpg format.A machine learning (ML) specialist wants to build an automated document processing workflow to extract text from specific fields from the documents and to classify the documents.The ML specialist wants a solution that requires low maintenance.Which solution will meet these requirements with the LEAST operational effort?Read More →