Activation Output

Activation output refers to the result produced by a specific function within a neural network's node (or neuron) after it processes input data. Think of it like a decision or a signal generated when certain conditions are met, helping the network decide what information is important. This output determines whether the neuron "fires" or passes its information forward. Different activation functions (like ReLU or sigmoid) shape this output, influencing how the network learns and makes predictions. In essence, activation output is the transformed signal that helps the neural network understand and process complex patterns.