In his "Deep learning with Python" book, Francois Chollet says that "With neural networks, it's safe to input missing values as 0, with the condition that 0 isn't already a meaningful value. The network will learn from exposure to the data that the value 0 means missing data and will start ignoring the value."
As I know, the input value 0 has not any effect in the neural network, since it cancels the corresponding weight after multiplication. So,
Q1. Why Chollet says that the network will learn to ignore the value? I think it is not necessary to learn; the network will ignore values 0 without learning!
Q2. Why he says that "with the condition that 0 isn't already a meaningful value. As I said, the value 0 cannot carry any meaning, because it has not any effect in the network.