DESCRIPTION: This program implements a three layer neural network which learns a pattern in the given matrix using only numpy as the dependency. This is primitive nerual network and currently uses only four inputs to predict the pattern and diminsih the errors in further predictions.
NEURAL NETWORK STRUCTURE: Number of nodes in the input layer (layer0) = 3 Number of nodes in the hidden layer (layer1)= 4 Number of nodes in the output layer (layer2)= 1 Please have a look at the NetworkStructure.png file in the repo.
SAMPLE INPUT/OUTPUT STRUCTURE: INPUT OUTPUT [0, 0, 1] [0] [0, 1, 1] [1] [1, 0, 1] [1] [1, 1, 1] [0]