np.random.float
numpy.random.uniform(low=0.0, high=1.0, size=None)np.random.float
numpy.random.uniform(low=0.0, high=1.0, size=None)numpy random int
np.random.randint(2, size=10) # Creates binary sample of size 10
np.random.randint(5, size=10) # Creates sample with 0-4 as values of size 10
np.random.randint(5, size=(2, 4))generate random integer matrix python
import numpy as np
randi_arr = np.random.randint(start, end, dimensions)
#random integers will be sampled from [start, end) (end not inclusive)
#end is optional; if end is not specified, random integers will be sampled from [0, start) (start not inclusive)
#dimensions can be specified as shown here; (m,n) #2D array with size 'm x n'np.rand.randint
np.random.randint(0,10, size=(5, 5)) # random integers from 0 to 10 in size 5,5
#o/p
array([[3, 9, 2, 3, 5],
[2, 8, 7, 7, 1],
[8, 2, 1, 1, 9],
[9, 0, 5, 6, 4],
[1, 6, 6, 4, 6]])np.random.randint to generate -1 +1
2 * np.random.randint(2, size=10) -1np.random.randn()
>>> 2.5 * np.random.randn(2, 4) + 3
array([[-4.49401501, 4.00950034, -1.81814867, 7.29718677], #random
[ 0.39924804, 4.68456316, 4.99394529, 4.84057254]]) #randomCopyright © 2021 Codeinu
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