Welcome to gradient backpropagation! This is the core algorithm that allows neural networks to learn. In this introduction, we'll explore how networks calculate gradients to update their weights. The process involves a forward pass to compute predictions, followed by a backward pass to propagate errors and calculate gradients for each weight in the network.