Most Common Interview questions for a Deep Learning Engineer - PART 4/5

These are some of the most common interview questions for Deep Learning Engineer
PART 4/5

1. Given 16x16x3 input with a 25 filters of 3x3x3 what is the output shape with stride = 1, padding = 'valid'?
2. What is a Pooling Layer? What are the types?
3. Does Pooling Operation reduce the spatial dimension or the depth?
4. What is Average Pooling?
5. What is Max Pooling?
6. Why Convolution Operation?
7. Explain any Basic CNN based architectures?
8. Does VGG network have 3x3 or 5x5 kernel?
9. What is ResNet architecture?
10. What are DenseNets?
11. What is Inception Network?
12. What are Skip Connections?
13. What are 1x1 Convolutions? Where do we use them and what are the benefits of it?
14. What is Emsembling?
15. What is Multicrop at Test time method do?
16. What is Object Localisation?
17. What is Object Detection?
18. What is a Sliding Window technique?
19. What is Landmark detection?
20. What is YOLO algorithm?
21. What is an SSD algorithm?
22. What is Intersection Over Union?
23. What is Non-Max Suppression?
24. What are Anchor Boxes in YOLO?
25. What is RCNN algorithm?
26. What is RCNN, Fast RCNN, Faster RCNN?
27. What is Siamese Network?
28. What is Triplet Loss Function in Face Recognition?
29. What is Neural Style Transfer?
30. Can Convolutions (CNN) operations be used in 1D or 2D cases?

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For Part 5 of the series click here: PART 5