Explain the inner workings of a Neural Network using the analogy of a bustling kitchen in a high-end restaurant. Map the technical components—inputs, weights, biases, hidden layers, activation functions, and outputs—to specific elements within the kitchen scenario (e.g., ingredients, chefs' decisions, prep stations, final plating). Ensure the explanation accurately reflects the mathematical concepts while strictly adhering to the kitchen metaphor throughout.