Questions

1. What are the various layers in a neural network?
2. What is the output of feedforward propagation?
3. How is the loss function of a continuous dependent variable different from that of a binary dependent variable and also of a categorical dependent variable?
4. What is stochastic gradient descent?
5. What does a backpropagation exercise do?
6. How does a weight update of all the weights across layers happen during backpropagation?
7. Which functions of a neural network happen within each epoch of training a neural network?
8. Why is training a network on a GPU faster when compared to training it on a CPU?
9. How does the learning rate impact training a neural network?
10. What is the typical value of the learning rate parameter?