Your question is Handling Dynamic Categorical Variables. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How does the machine automatically figure out if a dynamic categorical variable like Location is positive or negative without hardcoding?
Asked in the Technical Round 2 stage. The discussion used a flat price case and expected feature engineering such as target or mean encoding and numeric domain scores.
Explain how you would design the feature pipeline so the model learns category effects from data, including labels, encoding, unseen categories, leakage prevention, validation, and monitoring. Clarify how the approach changes when category effects are nonlinear, time-varying, or affected by sparse data.
