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  1. So setting up a neural network like this, in the end it all works out quite well. Training the network on the non-trivial question 'is it a bird, is it a plane ?' and training it on the following 2 examples : beak = 0, engine =1 : plane beak = 1, engine = 0 : bird just takes a second or so and fewer than 10000 iterations to reduce the error to less than 0.000x Increasing the nr of neurons in the hidden layers decreases the nr of iterations Interestingly once in a while the network is unable to converge and comes up with 0.5 as the answer, equivalent to 'I don't know' on a
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