Most Common Interview questions for a Machine Learning Engineer - PART 1/2

These are some of the most common interview questions for Machine Learning Engineer
PART 1/2

1. What are the types of Learning Algorithms?
2. What is Supervised Learning? And name its basic types?
3. What is Unsupervised Learning? And name its basic types?
4. What is a Linear Regression?
5. What is Logistic Regression?
6. What is a Cost Function?
7. What is a Convex Function?
8. What is Local Optima?
9. What is a Squared Error function?
10. What is the Cost function used for a Regression problem?
11. What is the Cost function used for a Classification Problem?
12. What is Gradient Descent?
13. What is the Learning Rate?
14. Is it necessary to change the learning rate during the training period?
15. What is Multi-Variate Linear Regression?
16. What is the difference between a Linear and Logistic Regression algorithm?
17. What is Feature Scaling?
18. What is Mean Normalization?
19. Is it better to have a small or large learning rate?
20. What is Feature Engineering?
21. What is Polynomial Regression?
22. What are the activation functions used in Linear Regression?
23. What are the activation functions used in Logistic Regression?
24. What are the different Optimization Algorithms?
25. Explain Gradient Descent, Conjugate gradient, BFGS, L-BFGS. What are the advantages and disadvantages of it? (This is a tough question)
26. What is multi-class classification and how do we do it ?
27. What is overfitting and underfitting ?
28. How do we address overfitting and underfitting?
29. What is High Bias?
30. What is High Variance?

The Best Books recommended to improve your Machine Learning skills:

   

I would also suggest having a look at the Udacity course Become a machine learning engineer.

For Part 2 of the series click here: PART 2