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)
