Microsoft Azure AI Fundamentals (AI-900)Describe fundamental principles of machine learning on AzureMedium
A retail company wants to analyze customer purchasing behavior to identify distinct groups of customers with similar buying patterns, without any prior knowledge of what these groups might be. They aim to tailor marketing strategies to these identified segments. Which type of machine learning would be most suitable for this task?
- AUnsupervised Learning
- BSemi-supervised Learning
- CSupervised Learning
- DReinforcement Learning
Show answer & explanationAnswer & explanation
Correct answer: A. Unsupervised Learning
Since the goal is to find distinct groups without any predefined labels or prior knowledge of customer segments, Unsupervised Learning, specifically clustering, is the most suitable approach.
Why the other options are wrong
- B. Semi-supervised learning uses a small amount of labeled data with a large amount of unlabeled data, but the core problem here is purely finding groups without labels.
- C. Supervised learning requires labeled data (predefined customer groups), which is not available here.
- D. Reinforcement learning involves an agent learning through rewards in an environment, which is not applicable to finding customer segments.
Unsupervised Learning
A type of machine learning that finds patterns or structures in unlabeled data, without human intervention.
- Works with data that has no predefined output labels.
- Common tasks include clustering, dimensionality reduction, anomaly detection.
- Used for exploratory data analysis, customer segmentation, data compression.
Memory trick: Learning: With a Teacher or Discovery Alone