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 a Neural Network?
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
How many kinds of nns exist?
List some commercial practical applications of artificial neural networks?
Explain Generative Adversarial Network.
Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned
What are the population, sample, training set, design set, validation set, and test set?
Explain neural networks?
What are conjugate gradients, levenberg-marquardt, etc.?
How are nns related to statistical methods?
What learning rate should be used for backprop?
How artificial neurons learns?
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