Machine Learning Specialty (Page 6)

A retail company stores 100 GB of daily transactional data in Amazon S3 at periodic intervals.The company wants to identify the schema of the transactional data.The company also wants to perform transformations on the transactional data that is in Amazon S3.The company wants to use a machine learning (ML) approach to detect fraud in the transformed data.Which combination of solutions will meet these requirements with the LEAST operational overhead? (Choose three.)Read More →

A Machine Learning Specialist works for a credit card processing company and needs to predict which transactions may be fraudulent in near-real time.Specifically, the Specialist must train a model that returns the probability that a given transaction may fraudulent.How should the Specialist frame this business problem?Read More →

A machine learning (ML) specialist is developing a deep learning sentiment analysis model that is based on data from movie reviews.After the ML specialist trains the model and reviews the model results on the validation set, the ML specialist discovers that the model is overfitting.Which solutions will MOST improve the model generalization and reduce overfitting? (Choose three.)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 →

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 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 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 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 →

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 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 →