1 Simple forward pass of one layer neural network in Python, with numpy
# -*- coding: utf-8 -*- """ Created on Fri Mar 18 12:39:21 2022 @author: Balaji """ import numpy as np num_neurons = 2; num_inputs = 3; num_dataSets= 1; print('\n Program for a simple neural network, doing a forward pass with one layer') print('\n Each row is a data set') inputs = np.random.randn(num_dataSets,num_inputs); weights = np.random.randn(num_neurons ,num_inputs); bias = np.random.randn(num_neurons ,1); results = np.zeros_like(bias) print('\n Input = ') print(inputs) print('\n Weights = ') print(weights) print('\n Bias = ') print(bias) for input_iter in inputs: for weight_iter,bias_iter,result_iter in zip(weights,bias,results): print('\n Input data set:') print(input_iter); print('\n is multiplied with weights') print(weight_iter) print('\n and added with bias') print(bias_iter) print('\n to give the result of neuron as') result_iter = input_iter.dot(weight_iter) + bias_iter; print(result_iter)
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