importnumpyasnp# 阶跃函数defstep_function(x):# x 为 np.arrayreturnnp.array(x>0,dtype=np.int_)# sigmoid 函数 (连续、可微)defsigmoid(x):return1/(1+np.exp(-x))# relu 函数 (连续、更简单)defrelu(x):returnnp.maximum(0,x) 2、点乘 np.dot(a, b) 规则(1) 当 a 和 b 都是一维数...
This python package (availabe on PyPI athttps://pypi.org/project/numpngw/) defines the functionwrite_pngthat writes a numpy array to a PNG file, and the functionwrite_apngthat writes a sequence of arrays to an animated PNG (APNG) file. Also included is the classAnimatedPNGWriterthat can...
b1 =np.random.randn(25,) b2 = np.random.randn(10,) 实现前向传播 使用前向传播部分中的公式。 为了方便起见,定义一个函数来乘以θ和X def z_calc(X, theta): return np.dot(X, theta.T) 我们也将多次使用激活函数。同样定义一个函数 def sigmoid(z): return 1/(1+ np.exp(-z)) 现在我将逐...
import numpy as np import math import matplotlib.pylab as plt import sys In [128] # 与门 def AND(x1,x2): # input = np.array([x1,x2]) # weight = np.array([0.5,0.5]) # b = 0 # if b+np.sum(input*weight) < 1: # return 0 # else: # return 1 return x1*x2 def test...
import numpy as np #Input array X=np.array([[1,0,1,0],[1,0,1,1],[0,1,0,1]]) #Output y=np.array([[1],[1],[0]]) #Sigmoid Function def sigmoid (x): return 1/(1 + np.exp(-x)) #Derivative of Sigmoid Function ...
For example,math.sinandnp.sinagree with AVX-512 disabled, but disagree by approximately2**-53(approximately double precision) depending on the input angle.np.cosis similar. I've also tested some of the other SIMD backed numpy functions, such asnp.expandnp.logand they also return non-zero ...
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import numpy as np import matplotlib.pyplot as plt np.random.seed(42) cat_images = np.random.randn(700, 2) + np.array([0, -3]) mouse_images = np.random.randn(700, 2) + np.array([3, 3]) dog_images = np.random.randn(700, 2) + np.array([-3, 3]) In the script abov...
importnumpyasnpimportpandasaspdfromnumpyimportrandomfromsklearn.datasetsimportload_breast_cancerX=load_breast_cancer().datay=load_breast_cancer().targetfromsklearn.preprocessingimportStandardScalersd=StandardScaler()X=sd.fit_transform(X)##记得 做标准化#定义sigmoid函数defsigmoid(x):return1.0/(1+np.exp...
import numpy as np def sigmoid(Z): """ Implements the sigmoid activation in numpy Arguments: Z -- numpy array of any shape Returns: A -- output of sigmoid(z), same shape as Z cache -- returns Z as well, useful during backpropagation """ A = 1/(1+np.exp(-Z)) cache = Z re...