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))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))Random Numbers in NumPy
from numpy import random
x = random.randint(100)
print(x)numpy random in python
import numpy as np
a=np.random.rand(5,2)
print(a)np.random.rand()
# train test split
df = pd.read_csv('file_location')
mask = np.random.rand(len(df)) < 0.8
train = df[mask]
test = df[~mask]Copyright © 2021 Codeinu
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