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The Hello World exampleIntroductionThe Hello World example demonstrates a regression model implemented as a neural network with an input layer of a single scalar value (the x parameter of y=sin(x)) , a hidden layer of 16 neurons and an output layer, again of a single scalar value (the y in y=sin(x)). To train the network a data set of 1000 values of the sin function is used onto which a small random noise is added. Once trained we can predict sin(x) for any value of x. Like most "Hello World" type programs this is pretty useless since we can get the precise value of sin(x) very easily, but it shows the principles of
Creating the data-set--![]() Comments |