Explain Generative Adversarial Network.

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How neural networks became a universal function approximators?

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 What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ‘computational’ rates a) (i) and (ii) are true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

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What is a Neural Network?

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How many kinds of kohonen networks exist?

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How many kinds of nns exist?

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Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

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 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

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How does an LSTM network work?

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 Which of the following is true for neural networks? (i) The training time depends on the size of the network. (ii) Neural networks can be simulated on a conventional computer. (iii) Artificial neurons are identical in operation to biological ones. a) All of the mentioned b) (ii) is true c) (i) and (ii) are true d) None of the mentioned

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What is the role of activation functions in a Neural Network?

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What is artificial intelligence neural networks?

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