A 3-input neuron is trained to output a zero when the input is 110 and a one when the input is 111. After generalization, the output will be zero when and only when the input is:
a) 000 or 110 or 011 or 101
b) 010 or 100 or 110 or 101
c) 000 or 010 or 110 or 100
d) 100 or 111 or 101 or 001
What are conjugate gradients, levenberg-marquardt, etc.?
How does ill-conditioning affect nn training?
How artificial neural networks can be applied in future?
How neural networks became a universal function approximators?
A 3-input neuron is trained to output a zero when the input is 110 and a one when the input is 111. After generalization, the output will be zero when and only when the input is: a) 000 or 110 or 011 or 101 b) 010 or 100 or 110 or 101 c) 000 or 010 or 110 or 100 d) 100 or 111 or 101 or 001
. Why are linearly separable problems of interest of neural network researchers? a) Because they are the only class of problem that network can solve successfully b) Because they are the only class of problem that Perceptron can solve successfully c) Because they are the only mathematical functions that are continue d) Because they are the only mathematical functions you can draw
How to avoid overflow in the logistic function?
A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0. a) True b) False c) Sometimes – it can also output intermediate values as well d) Can’t say
List some commercial practical applications of artificial neural networks?
What is artificial intelligence neural networks?
What are the applications of a Recurrent Neural Network (RNN)?
What is the role of activation functions in a Neural Network?
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