numpy.random.randn(d0, d1, …, dn) : creates an array of specified shape and fills it with random values as per standard normal distribution.
If positive arguments are provided, randn generates an array of shape (d0, d1, …, dn), filled with random floats sampled from a univariate “normal” (Gaussian) distribution of mean 0 and variance 1 (if any of the d_i are floats, they are first converted to integers by truncation). A single float randomly sampled from the distribution is returned if no argument is provided.
d0, d1, ..., dn : [int, optional]Dimension of the returned array we require, If no argument is given a single Python float is returned.
Array of defined shape, filled with random floating-point samples from the standard normal distribution.
Code 1 : randomly constructing 1D array
1D Array filled with randnom values : [-0.51733692 0.48813676 -0.88147002 1.12901958 0.68026197]
Code 2 : randomly constructing 2D array
2D Array filled with random values : [[ 1.33262386 -0.88922967 -0.07056098 0.27340112] [ 1.00664965 -0.68443807 0.43801295 -0.35874714] [-0.19289416 -0.42746963 -1.80435223 0.02751727]]
Code 3 : randomly constructing 3D array
3D Array filled with random values : [[[-0.00416587 -0.66211158] [-0.97254293 -0.68981333]] [[-0.18304476 -0.8371425 ] [ 2.18985366 -0.9740637 ]]]
Code 4 : Manipulations with randomly created array
3D Array filled with random values : [[[ 1.9609643 -1.89882763] [ 0.52252173 0.08159455]] [[-0.6060213 -0.86759247] [ 0.53870235 -0.77388125]]] Array * 3 : [[[ 5.88289289 -5.69648288] [ 1.56756519 0.24478366]] [[-1.81806391 -2.6027774 ] [ 1.61610704 -2.32164376]]] Array * 3 + 2 : [[[-2.73766306 6.80761741] [-1.57909191 -1.64195796]] [[ 0.51019498 1.30017345] [ 3.8107863 -4.07438963]]]
These codes won’t run on online-ID. Please run them on your systems to explore the working.
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