AWS Certified Machine Learning - Specialty MLS-C01 — Topic 1 Question 256

Question

A financial company sends special offers to customers through weekly email campaigns. A bulk email marketing system takes the list of email addresses as an input and sends the marketing campaign messages in batches. Few customers use the offers from the campaign messages. The company does not want to send irrelevant offers to customers. A machine learning (ML) team at the company is using Amazon SageMaker to build a model to recommend specific offers to each customer based on the customer's profile and the offers that the customer has accepted in the past. Which solution will meet these requirements with the MOST operational efficiency?

Accepted Answer

Correct answer: D. The correct answer is D. Option D: Use the Factorization Machines algorithm to build a model that can generate personalized offer recommendations for customers. Deploy a SageMaker batch inference job to generate offer recommendations. Feed the offer re... AWS Batch schedules and runs batch computing jobs at any scale without managing clusters. Amazon SageMaker builds, trains and deploys machine learning models in a fully managed service. Amazon Personalize builds real-time recommendation systems.

AWS Certified Machine Learning - Specialty MLS-C01 — Question 256