Question from the Deep learning - Fundamentals test

In shallow NN, a hidden layer can’t be made of more than 10 neurons whereas in deep NN, layers’ size is not bounded

In shallow neural networks, network can’t have more than 10 inputs whereas in deep learning, inputs’ number is not bounded

In shallow NN, neurons can’t use complex activation function (ex : ELU), whereas deep NN’ neurons can use any function they want

Shallow NN have 1 hidden layer whereas in deep NN the number of layer is not bounded