1. How would you explain Machine Learning to a school-going kid?
  2. How does Deep Learning differ from Machine Learning?
  3. Explain Classification and Regression
  4. What do you understand by selection bias?
  5. What do you understand by Precision and Recall?
  6. What is a Confusion Matrix?
  7. What is the difference between inductive and deductive learning?
  8. How is KNN different from K-means clustering?
  9. What is ROC curve and what does it represent?
  10. What’s the difference between Type I and Type II error?
  11. Is it better to have too many false positives or too many false negatives? Explain.
  12. Which is more important to you – model accuracy or model performance?
  13. What is the difference between Entropy and Information Gain?
  14. Explain Ensemble learning technique in Machine Learning.
  15. What is bagging and boosting in Machine Learning?
  16. What are collinearity and multicollinearity?

TOP MNC MACHINE LEARNING INTERVIEW QUESTIONS