Can you explain the difference between supervised and unsupervised learning?
Direct Answer
Repeated question focusing on core ML theory and practical application scenarios.
Why Interviewers Ask This
Essential knowledge for any data role. Ensures the candidate has a foundational understanding of algorithm categories.
How to Answer This Question
Clear definitions, examples of algorithms, and business contexts for each.
Key Points to Cover
- Labeled vs unlabeled
- Prediction vs discovery
- Examples
Sample Answer
Supervised learning uses labeled data to predict outcomes, like spam detection. Unsupervised learning finds patterns in unlabeled data, like customer segmentation. Both are vital for different business needs.
Common Mistakes to Avoid
- Confusing terms
- No examples
- Too technical jargon
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