Layer (Neural Network Layer)

Friendly Description: A layer is one rung on the ladder of a neural network. Information enters at the bottom, passes upward through layer after layer, and each one transforms it a little, picking up more meaning along the way. Stack enough layers, and simple inputs (like pixels) can become rich understandings (like "a smiling family photo").

Example: In an image recognition model, the first layer might just notice edges and colors. A few layers up, the network is identifying shapes like wheels and windows. By the top layer, it can confidently say, "This is a red sedan." Each layer built on what the one below it figured out.