nn-backpropogate 0.0.1

adding number

# Neural-Networks Contains Python Code for implemenation of various logic gates using BackPropogation in python Example Implementation of AND Gate using this Module ## Code >import NeuralNetwork >b=NeuralNetwork.BackPropogate(“and”) >b.selectEpochs(10000) >b.setLearningRate(0.1) >b.train() >b.print(“oo”) >b.showerror() >b.plot()

#### Print can take any of four parameter:- * ow1-Output Weights1 Array * ow2-Output Weights2 Array * ob-Output Biases Array * oo-Our Final Output ### Functions it includes- * sigmoid * drivative * train -Train Different Gates Model * showerror -Show Error Percentage from Expected Output * plot :- Plot different Grpahs for you * print :- Print can take 4 inputs depending on which it provides output * selectEpochs :- To select the number of epochs(Default :-1000) * setLearningRate :- To select the learning rate of your Model(Default-0.1)