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Proctor Level3_20

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  1. 1
    Show your ID card.
    Times asked 23
  2. 2
    Introduction.
    Times asked 9
  3. 3
    Explain your notebook/project.
    Times asked 21
  4. 4
    How many models did you train?
    Times asked 1
  5. 5
    On how many models did you perform Hyperparameter Tuning?
    Times asked 1
  6. 6
    Why did you perform Hyperparameter Tuning only on those models?
    Times asked 1
  7. 7
    Which model took the longest to train? Why?
    Times asked 1
  8. 8
    Explain Gradient Descent.
    Times asked 1
  9. 9
    Explain Gradient Descent on a whiteboard.
    Times asked 1
  10. 10
    Why did you use Accuracy instead of F1-Score or ROC-AUC?
    Times asked 1
  11. 11
    Draw and explain the Confusion Matrix.
    Times asked 1
  12. 12
    Write and explain the formulas for Precision, Recall, F1-Score, and Accuracy.
    Times asked 1
  13. 13
    How did you perform feature engineering on date/time features?
    Times asked 1
  14. 14
    Which hyperparameters did you tune?
    Times asked 2
  15. 15
    What time series model would you use?
    Times asked 1
  16. 16
    What more could you have done to improve the project?
    Times asked 1
  17. 17
    How did you handle class imbalance?
    Times asked 3
  18. 18
    What does the C parameter in Logistic Regression represent?
    Times asked 2
  19. 19
    Why did you use Median instead of Mean (or vice versa) for imputation?
    Times asked 1
  20. 20
    Which imputation technique would you use for a right-skewed feature?
    Times asked 1
  21. 21
    Which model did you use for the final submission?
    Times asked 1
  22. 22
    Show your Kaggle leaderboard score and rank.
    Times asked 2
  23. 23
    Show your Kaggle submissions.
    Times asked 1
  24. 24
    Questions based on your notebook implementation.
    Times asked 2
  25. 25
    Suggestions on improving the notebook/project.
    Times asked 1
  26. 26
    Asked if you have any questions for the proctor.
    Times asked 1
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