Questions & Answers

Instructor: Applied AI Course Duration: 30 mins

Revision Questions:

  1. What is Accuracy ?(
  2. Explain about Confusion matrix, TPR, FPR, FNR, TNR?(
  3. What do you understand  about Precision & recall, F1-score? How would you use it?(
  4. What is the ROC Curve and what is AUC (a.k.a. AUROC)?(
  5. What is Log-loss and how it helps to improve performance?.(
  6. Explain about R-Squared/ Coefficient of determination.(
  7. Explain about Median absolute deviation (MAD) ?Importance of MAD?(
  8. Define Distribution of errors?(

Self Learning:

  1. Which is more important to you– model accuracy, or model performance?
  2. Can you cite some examples where a false positive is important than a false negative?
  3. Can you cite some examples where a false negative important than a false positive?
  4. Can you cite some examples where both false positive and false negatives are equally important?
  5. What is the most frequent metric to assess model accuracy for classification problems?
  6. Why is Area Under ROC Curve (AUROC) better than raw accuracy as an out-of- sample evaluation metric?

**If you face any new Interview questions please put in comments ,we will work it out**

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