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AI0-001 AI Concepts and Techniques Practice Question

A natural language processing team wants to build a sentiment analysis model for customer reviews. They have 10,000 labeled reviews and 1 million unlabeled reviews. Which approach would MOST effectively leverage the unlabeled data?

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

Implement a semi-supervised learning algorithm that propagates labels from the labeled to the unlabeled data

Semi-supervised learning uses the small labeled set to guide learning from the large unlabeled set. Self-supervised learning would require a pretext task; fine-tuning a pre-trained model is also valid but semi-supervised directly addresses the labeled-unlabeled mix.

Answer analysis

Option-by-option breakdown

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

  • Use self-supervised learning to pretrain on the unlabeled data, then fine-tune on the labeled data

    Why it's wrong here

    Self-supervised learning is a valid approach, but semi-supervised learning is more direct when you have some labels and many unlabeled examples.

  • Train a supervised classifier on only the 10,000 labeled reviews

    Why it's wrong here

    Ignoring the unlabeled data wastes valuable information that could improve performance.

  • Implement a semi-supervised learning algorithm that propagates labels from the labeled to the unlabeled data

    Why this is correct

    Semi-supervised learning leverages the unlabeled data by using the labeled data to infer labels for similar unlabeled examples, improving model generalization.

  • Use reinforcement learning with the unlabeled data as rewards

    Why it's wrong here

    Reinforcement learning requires a reward signal from the environment, which is not available in this static dataset.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.