numpy.matlib.randn() — another function to do matrix operations in numpy. It returns a matrix of random values from a one-dimensional "normal" (Gaussian) distribution of mean 0 and variance 1.
Syntax: numpy.matlib.randn (* args)
Parameters:
* args: [Arguments] Shape of the output matrix. If given as N integers, each integer specifies the size of one dimension. If given as a tuple, this tuple gives the complete shape.If there are more than one argument and the first argument is a tuple then other arguments are ignored.Return: The matrix of random values drawn from the standard normal distribution.
Code # 1:
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Output:
Output matrix: [[ 0.78620217 0.41624612 -0.28417131 0.1071018] [0.77645105 0.30858858 -1.98901344 1.25977209] [0.26279443 -0.41026178 -0.60834494 2.82552737]]
Code # 2:
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Output:
Output matrix: [[0.34973625 0.28159132 0.72581405 -1.17511692 1.96773952]]
Code # 3:
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Output:
Output matrix: [[0.56784957 0.82980325 1.16683558] [-1.53444326 -0.27743273 0.65819067] [0.99654573 -1.20399432 -0.25603147] [1.74931585 0.58413453 1.67820029] [-1.25643231 0.21610229 0.21694595]]]
Note: src = "http://espressocode.top/images/aresconcoidili748083.jpg" /> we can use sigma * geek.matlib.randn (...) + mu .
For example, creating a 3 x 3 matrix with samples from 
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Code # 4:
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Output:
Output matrix: [[4.04967121 0.26982021 2.3503067] [5.57757131 2.40051874 -0.84588539] [7.43715651 3.84004412 1.40514615]]
