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 is Pooling in CNN and how does it work?
Which of the following is true? (i) On average, neural networks have higher computational rates than conventional computers. (ii) Neural networks learn by example. (iii) Neural networks mimic the way the human brain works. a) All of the mentioned are true b) (ii) and (iii) are true c) (i), (ii) and (iii) are true d) None of the mentioned
What are conjugate gradients, levenberg-marquardt, etc.?
How neural networks became a universal function approximators?
How does an LSTM network work?
Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned
Which is the similar operation performed by the drop-out in neural network?
What learning rate should be used for backprop?
What is the advantage of pooling layer in convolutional neural networks?
Why use artificial neural networks? What are its advantages?
How are artificial neural networks different from normal computers?
How does ill-conditioning affect nn training?
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