How Backpropagation Works — From Forward Pass to Gradient Updates

Backpropagation sounds like “sending errors backward.” But that explanation is too vague. The real question is: How does a neural network know which weights caused the error? That is what backpropagation solves. Core Idea Backpropagation is the mechanism that tells each parameter how much it contributed to the final loss. A neural network first makes a prediction. Then it measures the error. Then it sends gradient information backward through the network. That gradient tells the optimizer how to