def main(): X, Y = create2DData() plot2DData(X, Y) noOfLayers = 2 # Hidden and Output layer (Excluding the input layer) layerDimensions = [2, 3, 1] # No of units in Input, Hidden, Output layer noOfIterations = 6000 learningRate = 0.6 N = NeuralNet(noOfLayers, layerDimensions) # Create a object of Neural Net AL, WL, bL = N.gradientDescent(X, noOfIterations, learningRate, Y, printCost=True)
def main(): X, Y = generateOneDData() # plotOneDData(X, Y) noOfLayers = 2 # Hidden and Output layer (Excluding the input layer) layerDimensions = [1, 2, 1] # No of units in Input, Hidden, Output layer noOfIterations = 5000 learningRate = 0.6 N = NeuralNet(noOfLayers, layerDimensions) # Create a object of Neural Net AL, WL, bL = N.gradientDescent(X, noOfIterations, learningRate, Y, printCost=True) plotTransformedData(AL, WL, bL, Y)