Model y from x and interpret distributions

Scenario

You are given a dataset with one input feature x and a target y. The interviewer asks: “How would you model this?”

Later, you are shown a plot with two distributions (e.g., distribution of a feature for two groups/classes, or train vs. production) and asked to interpret what it implies.

Finally, you are asked several cold-start questions.

Tasks

1. Explain how you decide whether this is regression vs classification , what baseline models you try first, and what evaluation metrics you use.
2. Given a plot with two distributions, explain how you would:
   • Describe what you see (separation/overlap, shift, variance, multimodality)
   • Diagnose potential issues (label leakage, covariate shift, class imbalance, thresholding)
   • Decide next steps (feature engineering, calibration, sampling, monitoring)
3. Describe practical cold start strategies for:
   • New users
   • New items (videos)
   • New regions/languages

Assume you care about both predictive quality and production robustness.