My interview process at Micron was conducted online through a video call for a Machine Learning Engineering position with a specialization in computer vision. My interview was scheduled with the Technical Manager and one senior engineer.

1. Give your introduction.

2. Questions about MS Project - Image Processing:

   • What you do in that project.
   • What were your findings.

3. One question about explaining the Ph.D. research work in short.

4. What kind of models are used in research: regression or classification?

5. What was the input/output dataset for your model?

6. What preprocessing technique did you apply to your data?

7. What is R2 score and why do we use it?

8. What is adjusted R2 score?

9. What is bias and variance?

10. What is overfitting and underfitting? Explain them.

11. Techniques to overcome them.

12. Why you used RFR in your data:

    • Explain its working.
    • What is bagging and boosting?

13. What technique is used to determine the best hyperparameters?

14. What is cross-validation and why it is used?

15. What is feature engineering?

16. One question about CNN project work:

    • What layers I used and why.

17. Which activation function is used in the output layer of a CNN classification problem?

18. Difference between object classification and segmentation.

19. How can we convert spatial coordinates to an image?