The question list is as follows:

1. What is the difference between linear regression and neural networks?
2. What is the use of the activation function?
3. Why do we need to calculate the gradient in gradient descent?
4. What is the advantage of an RNN?
5. What are vanishing and exploding gradient problems?
6. What are gates in LSTM?
7. What is the use of the pooling layer?