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Computer VisioneasyMultiple ChoiceObjective-mapped

AI-103 Computer Vision Practice Question

When creating a new project in the Custom Vision portal, you need to choose a classification type. You want to tag an image with multiple independent tags (e.g., 'outdoor', 'sunset', 'mountain'). Which classification type should you select?

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

Multilabel

Multilabel classification allows zero or more tags to be applied to each image independently.

Answer analysis

Option-by-option breakdown

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

  • Multilabel

    Why this is correct

    Multilabel classification allows multiple tags to be assigned to a single image.

  • Object Detection

    Why it's wrong here

    Object detection provides bounding boxes, whereas classification tags the entire image.

  • Binary Classification

    Why it's wrong here

    Binary classification limits choices to two mutually exclusive options.

  • Multiclass

    Why it's wrong here

    Multiclass classification assigns exactly one tag per image.

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JA

Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official Microsoft exam blueprint

This AI-103 practice question is part of Courseiva's free Microsoft 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 AI-103 exam.