Can you explain what a neural network is and how it works?

Example Answer

The way I'd explain it in an interview is this: A neural network is a function approximator made of layers of weighted connections that transform inputs into outputs. Each layer learns intermediate representations, and nonlinear activation functions let the network model complex relationships rather than only simple linear ones.

During training, the network makes predictions, compares them with the target using a loss function, and then uses backpropagation and gradient-based optimization to update the weights. In practical terms, what makes neural networks powerful is not just the number of layers. It is their ability to learn useful hierarchical representations from raw or minimally processed inputs when the data and objective are well matched.

Common Poor Answer

A weak answer says a neural network is like the human brain and leaves it at that, which sounds familiar but does not actually explain layers, weights, activations, or training.