1. What is classifier in machine learning?
  2. What are the advantages of Naive Bayes?
  3. In what areas Pattern Recognition is used?
  4. What is Genetic Programming?
  5. What is Inductive Logic Programming in Machine Learning?
  6. What is Model Selection in Machine Learning?
  7. What are the two methods used for the calibration in Supervised Learning?
  8. Which method is frequently used to prevent overfitting?
  9. What is the difference between heuristic for rule learning and heuristics for decision trees?
  10. What is Perceptron in Machine Learning?
  11. Explain the two components of Bayesian logic program?
  12. What are Bayesian Networks (BN) ?
  13. Why instance based learning algorithm sometimes referred as Lazy learning algorithm?
  14. What are the two classification methods that SVM ( Support Vector Machine) can handle?
  15. What is ensemble learning?
  16. Why ensemble learning is used?

TOP MNC MACHINE LEARNING INTERVIEW QUESTIONS