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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 8399Neural 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 4679The 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 12621Which 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
How are artificial neural networks different from normal computers?
Why use artificial neural networks? What are its advantages?
What is backprop?
What can you do with an nn and what not?
What is a Neural Network?
What is simple artificial neuron?
Which is the similar operation performed by the drop-out in neural network?
How neural networks became a universal function approximators?
What is the advantage of pooling layer in convolutional neural networks?
How does ill-conditioning affect nn training?
Explain neural networks?
What are the disadvantages of artificial neural networks?
What is a neural network and what are some advantages and disadvantages of such a network?
What are conjugate gradients, levenberg-marquardt, etc.?
How are weights initialized in a network?
