def gradient_descent(X, y, w, b, learning_rate, iterations):
    m = len(y)

    for _ in range(iterations):
        predictions = X.dot(w) + b
        errors = predictions - y

        gradient_w = X.T.dot(errors) / m
        gradient_b = np.sum(errors) / m

        w = w - learning_rate * gradient_w
        b = b - learning_rate * gradient_b

    return w, b

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