Train one scalar weight to match a target using the same gradient-descent loop. Return the loss path instead of hiding the learning process.

def train_neuron(weight, target, learning_rate, steps):
    return [[step, weight, loss], ...]

• compute squared error against the target
• move the weight down the loss gradient
• record the weight and loss at every step