Deep Learning Intermediate Quiz 1

1. What is the main advantage of using convolutional layers in CNNs?

2. Which optimizer adapts an individual learning rate for each parameter?

3. What is dropout used for in deep learning?

4. Which layer is most often used for downsampling in CNNs?

5. How does a dense layer differ from a convolutional layer?

6. Which activation function is commonly used in hidden layers of deep networks?

7. What does batch normalization do?

8. Why is ReLU often preferred over sigmoid in deep networks?

9. What is a sequence model in deep learning?

10. Which of these is a sequence model?