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MLS-C01 Modeling Practice Question

A company is building a recommendation system for an e-commerce platform. They have user-item interaction data (clicks, purchases) and want to use matrix factorization. They plan to use Amazon SageMaker to train the model. Which dataset format is MOST appropriate for the built-in Factorization Machines algorithm?

⚠ Common exam trap

Test-takers frequently assume libsvm or CSV are universally optimal for sparse data, but SageMaker's built-in Factorization Machines specifically requires RecordIO-protobuf for native sparse tensor support and maximum performance, not just any text-based sparse format.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

RecordIO-protobuf with user_id, item_id, and label fields

The built-in Factorization Machines algorithm in Amazon SageMaker requires the RecordIO-protobuf format for optimal performance, as it allows efficient binary serialization and direct integration with SageMaker's distributed training infrastructure. This format supports sparse data representation, which is critical for high-dimensional user-item interaction data, and enables faster I/O and reduced memory overhead compared to text-based formats.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Libsvm format with user_id and item_id as features

    Why it's wrong here

    Libsvm is used for linear learners, not Factorization Machines.

  • CSV file with user_id, item_id, and label columns

    Why it's wrong here

    SageMaker's built-in FM does not support CSV input.

  • RecordIO-protobuf with user_id, item_id, and label fields

    Why this is correct

    RecordIO-protobuf is the required format for SageMaker's built-in Factorization Machines.

  • JSON lines file with user_id, item_id, and label fields

    Why it's wrong here

    JSON lines are not a supported format for built-in FM.

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This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.