Question
Which of the following is the layer that is responsible for the depth in deep learning?
- A. Convolution
- B. Dropout
- C. Pooling
- D. Hidden Correct
Explanation
The depth of a deep neural network is the number of hidden layers between the input and output layers; stacking many hidden layers is what makes a network deep. Convolution and pooling are specific layer types used in convolutional networks, and dropout is a regularization technique, so none of them on its own defines depth.
