Machine Learning Interview Questions 2023

As per my recent Interview experience I have created a list of questions on various Machine Learning Sections. This list will comprise of just questions, I am planning to write a separate blog post for all the answers.

Machine Learning Interview Questions

1. What is Regression?
2. What are the Types of regression?
3. Explain the assumptions of Linear regression.
4. How to evaluate regression models?
5. Explain different types of model Testing methods.
6. Explain Benefits of cross validation?
7. What is overfitting?
8. What are different ways to fix overfitting?
9. How to handle imbalanced data in a dataset?
10. What to do if your data is skewed?
11. What if your data has outliers, how to identify and different ways to fix?
12. What is difference between lasso and ridge regression?
13. What is cross entropy?
14. Difference between precision and recall?
15. What is a confusion matrix?
16. What is AUC?
17. What is bias variance trade-off?
18. What is correlation? How is it related to covariance?
19. What are activation function? Explain different Types? Where and why it is used? Sigmoid vs tan h vs relu?
20. What is classification?
21. How to evaluate classification models?
22. What are ensemble models?
23. What is clustering?
24. What are types of clustering?
25. How to decide the K in k means clustering? Can we automate it? If yes how?
26. What is hypothesis testing?
27. What is A/B testing?
28. How does time series work? Explain how to approach a time series problem step by step.
29. How do you treat seasonality in time series?
30. What to do if your time series data is not stationary?
31. Difference between ARIMA and SARIMA?
32. What is auto correlation?
33. Can we use deep learning for time series forecasting? If yes what models to use? How do they work?
34. What is null hypothesis?