28th
Jul
Neural Networks MCQ

Neural Networks MCQ

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  • 28th Jul, 2021
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Neural Networks MCQ

Following are mostly asked Neural networks MCQ test that are designed for professionals like you to crack you interviews. You can take this Neural networks online test before appearing to you real interview. This Neural networks quiz there are around 30+ multiple choice questions on Neural networks with four options.

1) What is perceptron?

  • A. neural network that contains feedback
  • B. an auto-associative neural network
  • C. double layer auto-associative neural network
  • D. a single layer feed-forward neural network with pre-processing

2) What is Neuro software?

  • A. It is powerful and easy neural network
  • B. A software used to analyze neurons
  • C. Designed to aid experts in real world
  • D. It is software used by Neurosurgeon

3) Which is true for neural networks?

  • A. It has set of nodes and connections
  • B. Each node computes it’s weighted input
  • C. Node could be in excited state or non-excited state
  • D. All of the Above

4) Who was the inventor of the first neurocomputer?

  • A. Dr. Alex Hecht-Nielsen
  • B. Dr. John Hecht-Nielsen
  • C. Dr. Robert Hecht-Nielsen
  • D. Dr. Steve Hecht-Nielsen

5) How many types of Artificial Neural Networks?

  • A. 2
  • B. 3
  • C. 4
  • D. 5
Download Free : Neural Networks MCQ PDF

6) In which ANN, loops are allowed?

  • A. FeedBack ANN
  • B. FeedForward ANN
  • C. Both A and B
  • D. None of the above

7) What is the full form of BN in Neural Networks?

  • A. Bayes Nets
  • B. Belief Networks
  • C. Bayesian Networks
  • D. All of the Above

8) What is Neuro software?

  • A. A software used to analyze neurons
  • B. It is powerful and easy neural network
  • C. It is software used by Neurosurgeon
  • D. Designed to aid experts in real world

9) Neural Networks complex are ______

  • A. Linear Functions
  • B. Discrete Functions
  • C. Nonlinear Functions
  • D. Exponential Functions

10) The output at each node is called_____

  • A. Axons
  • B. Weight
  • C. Neurons
  • D. Node value

11) Full form of ANNs ______

  • A. AI Neural Networks
  • B. Artificial Neural Node
  • C. Artificial Neural numbers
  • D. Artificial Neural Networks

12) The first artificial neural network was invented in _____

  • A. 1948
  • B. 1958
  • C. 1968
  • D. 1978

13) The fundamental unit of network is

  • A. Axons
  • B. Brain
  • C. Nucleus
  • D. Neuron

14) In neural how can connectons between different layers be achieved?

  • A. interlayer
  • B. intralayer
  • C. Both A and B
  • D. None of the above

15) What is STM in neural network?

  • A. short term memory
  • B. short topology memory
  • C. stimulated topology memory
  • D. All of the Above

16) Who invented perceptron neural networks?

  • A. Widrow
  • B. Rosenblatt
  • C. McCullocch-pitts
  • D. Minsky & papert

17) What is ART in neural networks?

  • A. Artificial resonance theory
  • B. Adaptive resonance theory
  • C. Automatic resonance theory
  • D. None of the above

18) What is approx size of neuron body(in micrometer)?

  • A. below 5
  • B. 5-10
  • C. 10-80
  • D. above 100

19) Which of the following is true for neural networks?

  • A. It has a set of nodes and connections
  • B. Each node computes it’s weighted input
  • C. A node could be in an excited state or non-excited state
  • D. All of the Above

20) What is the full form of BN in Neural Networks?

  • A. Bayes Nets
  • B. Belief Networks
  • C. Bayesian Networks
  • D. All of the Above

21) Which of the following is an Applications of Neural Networks?

  • A. Aerospace
  • B. Electronics
  • C. Automotive
  • D. All of the Above

22) Artificial neural network(ANN) used for______

  • A. Clustering
  • B. Classification
  • C. Pattern Recognition
  • D. All of the Above

23) In which neural net architecture, does weight sharing occur?

  • A. Recurrent Neural Network
  • B. Convolutional neural Network
  • C. Fully Connected Neural Network
  • D. All of the Above

24) 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

25) Which of the following is an application of NN (Neural Network)?

  • A. Sales forecasting
  • B. Data validation
  • C. Risk management
  • D. All of the Above

26) Automated vehicle is an example of ______.

  • A. Active learning
  • B. Unsupervised learning
  • C. Supervised learning
  • D. Reinforcement learning

27) Decision Nodes are represented by

  • A. Disks
  • B. Squares
  • C. Circles
  • D. Triangles

28) Chance Nodes are represented by

  • A. Disks
  • B. Squares
  • C. Circles
  • D. Triangles

29) End Nodes are represented by

  • A. Disks
  • B. Squares
  • C. Circles
  • D. Triangles

30) How the decision tree reaches its decision?

  • A. No test
  • B. Two test
  • C. Single test
  • D. Sequence of test

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