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Who is concerned with nns?
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What are neural networks and how do they relate to ai?
What is backprop?
What can you do with an nn and what not?
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 learning rate should be used for backprop?
How are weights initialized in a network?
How artificial neurons learns?
. Why are linearly separable problems of interest of neural network researchers? a) Because they are the only class of problem that network can solve successfully b) Because they are the only class of problem that Perceptron can solve successfully c) Because they are the only mathematical functions that are continue d) Because they are the only mathematical functions you can draw
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
What are cases and variables?
The name for the function in question 16 is a) Step function b) Heaviside function c) Logistic function d) Perceptron function
Explain Generative Adversarial Network.
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