Why is a deep neural network better than a shallow neural network?

Deep neural networks (DNNs) excel over shallow networks due to their ability to learn hierarchical representations of data. Each successive layer in a DNN can capture increasingly complex and abstract features, leading to superior performance on intricate tasks. While shallow networks might suffice for simpler problems or when computational resources and latency are critical constraints, DNNs offer greater capacity for generalization and modeling complex patterns.