AI Neural Networks Interview Preparation Guide
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Artificial Intelligence Neural Networks frequently Asked Questions in various AI Neural Networks job Interviews by interviewer. Get preparation of Artificial Intelligence Neural Networks job interview

26 AI Neural Networks Questions and Answers:

1 :: What is Artificial Intelligence Neural Networks?

For the sake of trying to produce intelligent behavior however really all that's being done is work with artificial neural networks where each cell is a very simple processor and the goal is to try and make them work together to solve some problem. That's all that gets covered in this book. Many people are skeptical that artificial neural networks can produce human levels of performance because they are so much simpler than the biological neural networks.
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3 :: Explain Neural Networks?

A neural network can be defined as a model of reasioning
based on the human brain.
The human brain incorporates nearly 10 billion neurons and
60 trillion connections,Synapses,between them.
By using multiple neurons simultaneously,the brain can
perform its functions much faster than the faster computers.

Although a single neuron has a very simple structure,an
army of such elements constitutes a tremendous processing
power.
The network which represents the connections among several
neurons is called a neural network.
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4 :: Explain Artificial Neural Networks (ANNs)?

A computing system made up of a number of simple, highly interconnected processing elements, which process information by their dynamic state response to external inputs.
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6 :: 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

c) It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn.
Explanation:
Back propagation is the transmission of error back through the network to allow weights to be adjusted so that the network can learn.
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8 :: 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

b) Because they are the only class of problem that Perceptron can solve successfully
Explanation:
Linearly separable problems of interest of neural network researchers because they are the only class of problem that Perceptron can solve successfully
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