Which layer in a neural network produces the final predictions?

• A. Hidden layer
• B. Input layer
• C. Output layer
• D. Activation layer

Answer: (C)

In a neural network, the final predictions come from the last layer, the output layer. This layer takes the high-level representations formed by the earlier layers and maps them into the format needed for the task—such as class probabilities for classification or a numeric value for regression. The output layer is responsible for producing the actual values you compare to the ground truth during training. Activation functions are usually applied within this final layer (or its neurons) to produce the appropriate output range, like softmax for multi-class probabilities, sigmoid for binary decisions, or a linear value for regression. The other layers are intermediaries that transform data; the input layer merely holds the data, and hidden layers refine the features.