Implement a single neuron from first principles: weighted sum, bias, then ReLU. Make the scalar output explicit before adding training.

def neuron_forward(weights, inputs, bias):
    return activation(weighted_sum)

• pair each weight with one input
• add the bias before activation
• ReLU clamps a negative score to zero