NumPy broadcasting for vectorized feature engineering

                  import numpy as np

features = np.array([
    [120.0, 3.0, 10.0],
    [90.0, 5.0, 7.0],
    [150.0, 2.0, 14.0],
])

mean = features.mean(axis=0)
std = features.std(axis=0)
standardized = (features - mean) / std

weights = np.array([0.5, 1.5, 2.0])
weighted_score = standardized * weights
final_score = weighted_score.sum(axis=1)

print(final_score)