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MLS-C01 · Question #288

MLS-C01 Question #288: Real Exam Question with Answer & Explanation

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ML Implementation and Operations

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?

Options

  • AUse the Factorization Machines algorithm to build a model that can generate personalized offer
  • BUse the Neural Collaborative Filtering algorithm to build a model that can generate personalized
  • CUse the Neural Collaborative Filtering algorithm to build a model that can generate personalized
  • DUse the Factorization Machines algorithm to build a model that can generate personalized offer

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Topics

#Recommendation Systems#Collaborative Filtering#Amazon SageMaker#Operational Efficiency
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