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What is a neural network and what are some advantages and disadvantages of such a network?
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How many kinds of nns exist?
What are neural networks? What are the types of neural networks?
What is simple artificial neuron?
Explain Generative Adversarial 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
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
How artificial neurons learns?
What are the disadvantages of artificial neural networks?
What are the population, sample, training set, design set, validation set, and test set?
How are artificial neural networks different from normal computers?
What are the different layers in CNN?
What are the applications of a Recurrent Neural Network (RNN)?
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