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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 8272Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions
1 13231A 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 7177The name for the function in question 16 is a) Step function b) Heaviside function c) Logistic function d) Perceptron function
1 4749Having 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 4572The 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 12486Which 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 7739Post New AI Neural Networks Questions
How artificial neurons learns?
How neural networks became a universal function approximators?
How are weights initialized in a network?
What is backprop?
What are combination, activation, error, and objective functions?
Who is concerned with nns?
What is Pooling in CNN and how does it work?
How are artificial neural networks different from normal computers?
Are neural networks helpful in medicine?
What are cases and variables?
Why use artificial neural networks? What are its advantages?
Describe the structure of artificial neural networks?
How are layers counted?
How human brain works?
How does ill-conditioning affect nn training?
