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In: AI, Autonomous Vehicles, Deep Machine Learning

Start by building a very simple network: import numpy as np class NeuralNetwork: def __init__(self, x,y): self.input = x self.y = y self.Weights1 = np.random.randn(self.input.shape[1],5) self.Weights2 = np.random.randn(5,1) self.output = np.zeros(self.y.shape) def sigmoid_z(self,x): #create a sigmoid function z = 1/(1 + np.exp(-x)) return z def sigmoid_z_derivative(self,x): return self.sigmoid_z(x)*(1-self.sigmoid_z(x)) def forwardpropogation(self):Continue Reading

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In: Math, Science

R Squared is the coefficient of determination it normally ranges from 0 to 1, and provides a measure of how well observed outcomes, are replicated by the model.   The formula is: Residual(Error) sum of squares (RSS), also known as (SSR) , is the sum of the squares of theContinue Reading