Answer / Rupak Ranjan

Generative Adversarial Network (GAN) is a type of deep learning model that consists of two parts: a generator and a discriminator. The generator creates new samples, while the discriminator tries to distinguish between real and generated samples. Through a minimax game between these two networks, GANs can learn to generate realistic data.

Explain neural networks?

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How to avoid overflow in the logistic function?

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 Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in a picture are connected or not a) (ii) and (iii) are true b) (ii) is true c) All of the mentioned d) None of the mentioned

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 What is back propagation? a) It is another name given to the curvy function in the perceptron b) It is the transmission of error back through the network to adjust the inputs c) It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn. d) None of the mentioned

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What are neural networks and how do they relate to ai?

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 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

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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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 Neuro software is: a) A software used to analyze neurons b) It is powerful and easy neural network c) Designed to aid experts in real world d) It is software used by Neuro surgeon

2 Answers   Bihar State Power Holding Company Limited BSPHCL,

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What are the different layers in CNN?

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What are neural networks? What are the types of neural networks?

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What are the population, sample, training set, design set, validation set, and test set?

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What is the advantage of pooling layer in convolutional neural networks?

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