One of the questions at the panel interview focused on how to handle high-cardinality categorical variables in a model, especially when a naive approach could introduce noise or performance issues. The discussion was very practical and centered on trade-offs rather than theoretical tricks.
Why are you interested in DS job
Typical questions about motivation, interests, and experience.
what my main Motivation to work there was
- Difference between frequency and bayesian approaches - Bias-variance trade-off - How does Random Forest work - How to deploy a model through the cloud - Questions about different metrics
Q: Explain about my project
I have mentioned them above.
Explain your previous experiences related to the job position.
selection bias, how to define and address overfitting
Logistic regression based question SQL coding if target values are all positive then can prediction came out to be negative?
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