1. What is the difference between covariance and correlation?
  2. What is convex hull ?
  3. What cross validation technique would you use on time series data set? Is it k-fold or LOOCV?
  4. What do you understand by Type I vs Type II error ?
  5. When does regularization becomes necessary in Machine Learning?
  6. What do you understand by Bias Variance trade off?
  7. What Is Bias and Variance in a Machine Learning Model?
  8. What Is the Trade-off Between Bias and Variance?
  9. Define Precision and Recall.
  10. What Is Decision Tree Classification?
  11. What Is Pruning in Decision Trees, and How Is It Done?
  12. Briefly Explain Logistic Regression.
  13. Explain the K Nearest Neighbor Algorithm.
  14. What Is a Recommendation System?
  15. What Is Kernel SVM?

TOP MNC MACHINE LEARNING INTERVIEW QUESTIONS