How does Numpy normalize the matrix of 5 to 5?

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Normalize a 5-5 matrix

Import numpy as np

Tang_array = np.random.random ((5)) tang_max = tang_array.max () tang_min = tang_array.min () tang_array = (tang_array-tang_min) / (tang_max-tang_min) print (tang_array)

Print the results:

[[0.18134559 0.36496096 0.5232671 0.52860662 0.74265158] [0.31451177 0.87817493 0.59569668 0.57995506 0.22251323] [0.72361002 0.4825004 0.96024183 0. 0.10695723] [0.9537164 0.00109582 0.43241363 0.67049173 0.18956681] [0.89488491 0.27914115 0.90429462 0.12998232 1.] Thank you for reading. The above is the content of "how Numpy normalizes the matrix of 5 to 5". After the study of this article, I believe you have a deeper understanding of the problem of how Numpy normalizes the matrix of 5 to 5. The specific use situation still needs to be verified by practice. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!