Fully Connected Layer

A fully connected layer is a component in a neural network where every input is connected to every output. Think of it like a group discussion where each person shares their thoughts with everyone else. In this layer, each input contributes to each output, allowing the model to learn complex patterns. The connections are weighted, meaning some inputs matter more than others, which helps the network make better predictions based on the information it has learned. This layer typically appears towards the end of the network, combining features extracted earlier to produce final decisions or classifications.