Most Common Interview questions for a Machine Learning Engineer - PART 2/2

These are some of the most common interview questions for Machine Learning Engineer

PART 2/2

1. How do we address High Bias and Variance scenarios?
2. What is regularization?
3. What happens if we reduce the number of features - what is affected bias or variance or both? Explain
4. What is L1 Regularisation?
5. What is L2 Regularisation?
6. Which is sparse - L1 or L2 regularisation?
7. What are Neural Networks?
8. What is Forward prop and Backward prop?
9. What is Gradient Checking?
10. How do we do weights initialization?
11. Explain a typical ML pipeline?
12. How do we evaluate a Learning algorithm?
13. How do we do the model selection?
14. What is Linear Regression with Regularisation?
15. Plot a graph of error Vs the number of training examples? The error is Cross-validation and Training losses.
16. Will collecting more data solve - high variance or bias?
17. What is Precision / Recall / F1 score ?
18. What is SVM?
19. Why is SVM called Large Margin Classifier?
20. What are the kernels in SVM? Name some kernels.
21. When to use Logistic Regression and SVM?
22. Is SVM a convex or concave function?
23. Does SVM have a global optimum?
24. What is unsupervised learning?
25. What are the types of unsupervised learning algorithms?
26. What is the K-Mean algorithm?
27. What is PCA?
28. Why is PCA used?
29. What is t-SNE?
30. What is the meaning of 99% of variance is retained mean in PCA?
31. What is Anomaly detection?
32. What is a Gaussian Distribution?
33. What is the difference between a Gaussian and Normal distribution?
34. What is Content-Based Recommendation?
35. What is Collaborative filtering?
36. What is Stochastic Gradient Descent?
37. What is Batch Gradient Descent?
38. What is Mini-Batch Gradient Descent?
39. What is Map-reduce?
40. Can you explain any ML pipeline with an example use case?
41. How do we do OCR?
42. What is a Decision Tree? Answer
43. What is a Random Forest? Answer

The Best Books recommended to improve your Machine Learning skills:

   

For Part 1 of the series click here: PART 1

For Deep Learning Interview Questions Please Check this series: Deep Learning