How to train ANN(Artificial Neural Network Part-2)
Hello friends today we are going to train the ANN to more accuracy values for Wights (W1,W2,W3) print ("asinment") import numpy as np from scipy import optimize from mpl_toolkits.mplot3d import axes3d import matplotlib.pyplot as plt import matplotlib.pyplot as plt1 import sys sys.setrecursionlimit(500) class Neural_Network(object): def __init__(self): self.inputLayerSize = 3 self.outputLayerSize = 1 self.hiddenLayer1Size = 4 self.hiddenLayer2Size = 3 #Weights (parameters) self.W1 = np.random.randn(self.inputLayerSize, self.hiddenLayer1Size) self.W2 = np.random.randn(self.hiddenLayer1Size,self.hiddenLayer2Size) self.W3 = np.random.randn(self.hiddenLayer2Size, self.outputLayerSize) #weights values #print("W1 : ",self.W1) #print("W2 : ",self.W2) #print("W3 : ",self.W3)
