更多机器学习知识请查收于： https://blog.csdn.net/weixin_45316122/article/details/109854595
Trick：纯demo，心在哪里，结果就在那里（ipython notebook代码演示）
2 import random for i in range(5): #生成0-1的随机浮点数 #random.random() print(i,random.random()) 0 0.772776376196428 1 0.6258100198861752 2 0.36015258471911005 3 0.09175725539333501 4 0.11489461483723162 4 import random for i in range(5): #生成指定范围的随机浮点数，a<=n<=b print(i,random.uniform()) """ random.uniform(a,b) 必须要有两个参数否则报错 TypeError: uniform() missing 2 required positional arguments: 'a' and 'b' """ --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-4-9a2f5817563e> in <module> 1 import random 2 for i in range(5): ----> 3 print(i,random.uniform()) TypeError: uniform() missing 2 required positional arguments: 'a' and 'b' 7 import random for i in range(5): # 生成指定范围的随机整数，a<=n<=b print(i,random.randint(3,8)) """ random.randint(a,b) 必须要有两个参数否则报错 TypeError: uniform() missing 2 required positional arguments: 'a' and 'b' """ 0 8 1 4 2 8 3 4 4 4 8 import random for i in range(5): print(i,random.randrange(0,10,3)) """ random.randrange(start,stop,step) 指定范围内，按step递增的集合中的随机数，start<=n<stop """ --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-8-3a69614229f0> in <module> 1 import random 2 for i in range(5): ----> 3 print(i,random.randrange()) TypeError: randrange() missing 1 required positional argument: 'start' """ random.choice() 给定的集合中选择一个字符 random.sample() 给定的集合中采样多个字符 random.shuffle() 对给定集合重排列(洗牌) """ No output 11 #numpy.random import numpy as np np.random.rand(2,3) """ np.random.rand(d0,d1,...,dn) 返回n维的随机数矩阵。randn为正态分布 在这里需要注意。只会执行最后一个代码 """ np.random.rand() 11 0.8227630408345724 12 import numpy as np np.random.randint(1,5,[4,3]) """ np.random.randint(low[,high,size,dtype]) 返回low<=n<high范围的整数，random_integers为dtype=np.int类型 """ 12 array([[1, 1, 1], [2, 4, 1], [2, 4, 3], [3, 4, 2]]) 13 import numpy as np np.random.random(size = [3,3]) """ np.random.random(size) 返回指定size的[0,1)随机数矩阵，random_sample、ranf、sample和它一样 np.random.choice(a[,size,replace,p]) 含义类似于random.choice """" 13 array([[0.4403994 , 0.687003 , 0.25333792], [0.89981862, 0.4991398 , 0.34219562], [0.79770316, 0.05762094, 0.92834715]])
