A neural network consists of layers of interconnected nodes, or "neurons." These layers include an input layer, one or more hidden layers, and an output layer. Each neuron processes input data and passes the result to the next layer. The network adjusts its internal parameters through a training process, allowing it to improve its predictions over time.
