AI Neural Networks Interview Questions
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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

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Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

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A 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 6404

The name for the function in question 16 is a) Step function b) Heaviside function c) Logistic function d) Perceptron function

1 4076

Having 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 3774

The 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 11571

 Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned

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What is a Neural Network?

791

What is the role of activation functions in a Neural Network?

713

What is the difference between a Feedforward Neural Network and Recurrent Neural Network?

830

What are the applications of a Recurrent Neural Network (RNN)?

764

How are weights initialized in a network?

647

What is Pooling in CNN and how does it work?

719

Explain Generative Adversarial Network.

686

What are the different layers in CNN?

794


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Un-Answered Questions { AI Neural Networks }

How human brain works?

678


How are artificial neural networks different from normal computers?

873


What are neural networks and how do they relate to ai?

720


How neural networks became a universal function approximators?

686


What are neural networks? What are the types of neural networks?

742






How are weights initialized in a network?

647


Describe the structure of artificial neural networks?

631


What can you do with an nn and what not?

647


What is backprop?

657


How many kinds of kohonen networks exist?

707


How artificial neurons learns?

683


How to avoid overflow in the logistic function?

739


What are the applications of a Recurrent Neural Network (RNN)?

764


List some commercial practical applications of artificial neural networks?

841


Explain Generative Adversarial Network.

686