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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
1 8398Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions
1 13343A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0. a) True b) False c) Sometimes – it can also output intermediate values as well d) Can’t say
1 7286The name for the function in question 16 is a) Step function b) Heaviside function c) Logistic function d) Perceptron function
1 4864Having 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
1 4678The network that involves backward links from output to the input and hidden layers is called as ____. a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron
1 12620Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned
1 7852Post New AI Neural Networks Questions
What is the difference between a Feedforward Neural Network and Recurrent Neural Network?
How many kinds of nns exist?
How are weights initialized in a network?
How artificial neural networks can be applied in future?
What are the applications of a Recurrent Neural Network (RNN)?
What is backprop?
What are combination, activation, error, and objective functions?
What are the disadvantages of artificial neural networks?
Which is the similar operation performed by the drop-out in neural network?
Explain Generative Adversarial Network.
Describe the structure of artificial neural networks?
List some commercial practical applications of artificial neural networks?
How does ill-conditioning affect nn training?
what are some advantages and disadvantages of neural network?
What is simple artificial neuron?
