BACKPROBAGATION IN NEURAL NETWORK
Code Sample and Text Backpropagation In Python In the case of simple feedforward neural networks, the process of backpropagation can be done efficiently in Python. First, we will import the necessary libraries. import numpy as np Next, we will define a simple neural network with one hidden layer. def sigmoid(x): return 1.0 / (1 + np.exp(-x)) def sigmoid_derivative(x): return x * (1.0 - x) class NeuralNetwork: def __init__(self, x, y): self.input = x self.weights1 = np.random.rand(self.input.shape[1],4) self.weights2 = np.random.rand(4,1) self.y = y self.output = np.zeros(self.y.shape) def feedforward(self): self.layer1 = sigmoid(np.dot(self.input, self.weights1)) self.output = sigmoid(np.dot(self.layer1, self.weights2)) def backprop(self): # application of the chain rule to find d...