Basic Feedforward Neural Network

A feedforward neural network moves input features through one or more hidden layers to produce an output prediction. Each hidden layer learns a new representation of the data, using the weights and activation functions learned during training. This diagram gives a readable first view of that flow: features enter on the left, transformations occur in the hidden layers, and a prediction leaves on the right. It is suitable for a lesson, an architecture overview, or a model card introduction. It is not a detailed neuron-level drawing, so it does not show individual weights, bias terms, or activations. Add those only when the audience needs to inspect the mathematical model.