import numpy as np

def cost_fun_vectorized(x, y, w, b):
    m = len(x)
    pred = w * x + b
    err = pred - y
    return np.sum(err ** 2) / (2 * m)


distances_np = np.array([1, 2, 3, 4, 5])
actual_times_np = np.array([12, 17, 22, 27, 32])

print("Cost for w=4, b=10:", cost_fun_vectorized(distances_np, actual_times_np, w=4, b=10))
print("Cost for w=5, b=7:", cost_fun_vectorized(distances_np, actual_times_np, w=5, b=7))

# Cost for w=4, b=10: 1.0
# Cost for w=5, b=7: 0.0

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