Applied Scientist ML Breadth: Bias-Variance, Overfitting and Fundamentals

Problem Overview

The ML breadth part of Amazon's Applied Scientist interviews: a fast run of short conceptual questions across statistics, classic machine learning and deep learning, usually next to a coding question in a phone screen; three of the ten reports also mention a Leadership Principle question. Ten candidate reports describe it,…

• 12 candidate-reported follow-ups — the exact probes interviewers asked, with the trigger for each
• The rest of the problem statement — full requirements, constraints, and edge cases
• Approach and trade-offs — what passing candidates did, and the mistakes that sink people