Which of the following is not the promise of artificial neural network?
a) It can explain result
b) It can survive the failure of some nodes
c) It has inherent parallelism
d) It can handle noise
What are the population, sample, training set, design set, validation set, and test set?
Explain neural networks?
What is simple artificial neuron?
How many kinds of nns exist?
What are the applications of a Recurrent Neural Network (RNN)?
Having multiple perceptrons can actually solve the XOR problem satisfactorily: this is because each perceptron can partition off a linear part of the space itself, and they can then combine their results. a) True – this works always, and these multiple perceptrons learn to classify even complex problems. b) False – perceptrons are mathematically incapable of solving linearly inseparable functions, no matter what you do c) True – perceptrons can do this but are unable to learn to do it – they have to be explicitly hand-coded d) False – just having a single perceptron is enough
What is the role of activation functions in a Neural Network?
Explain Generative Adversarial Network.
Who is concerned with nns?
What is artificial intelligence neural networks?
How does ill-conditioning affect nn training?
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