AI0-001 AI Concepts and Techniques Practice Question
A company wants to use machine learning to recommend products to customers based on their purchase history. Which TWO techniques are appropriate for this task? (Select TWO)
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
✓
Collaborative filtering
Collaborative filtering recommends based on user similarities. K-Nearest Neighbors can find similar users or items. Both are suitable for recommendation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Collaborative filtering
Why this is correct
Collaborative filtering uses behavior patterns to recommend items.
- ✗
Principal Component Analysis (PCA)
Why it's wrong here
PCA is for dimensionality reduction, not recommendation.
- ✓
K-Nearest Neighbors (KNN)
Why this is correct
KNN can find similar users or items for recommendation.
- ✗
Naive Bayes
Why it's wrong here
Naive Bayes is for classification, not typically for recommendations.
- ✗
Linear regression
Why it's wrong here
Linear regression predicts continuous values, not recommendations.
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JA
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.