MLA-C01 ML Model Development Practice Question
Which SageMaker built-in algorithm is best suited for detecting anomalous login attempts based on IP addresses and user behavior?
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
✓
IP Insights
IP Insights is a built-in algorithm for learning IP address usage patterns and detecting anomalous behavior. The other algorithms are for different purposes: XGBoost for classification, K-Means for clustering, and PCA for dimensionality reduction.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
XGBoost
Why it's wrong here
XGBoost is for supervised learning, not specifically for IP anomaly detection.
- ✓
IP Insights
Why this is correct
IP Insights is designed to detect anomalous IP usage.
- ✗
PCA
Why it's wrong here
PCA is for dimensionality reduction.
- ✗
K-Means
Why it's wrong here
K-Means is for clustering, not specialized for IP analysis.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-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 MLA-C01 exam.