Neural Networks MCQ Questions And Answers

The following quiz “Neural Networks MCQ Questions And Answers” provides Multiple Choice Questions (MCQs) related to Neural Networks. These Neural Networks MCQs are also Interviews (campus interview, walk-in interview, company interview), Placement or recruitment, entrance examinations, and competitive examinations oriented. You can practice the below questions to improve your Neural network skills. You can click on the View Answer button to check the answer. Let’s solve this Neural Networks MCQ Questions And Answers Quiz. Neural networks, also known as artificial neural networks (ANNs) or simulated neural networks (SNNs), are a series of algorithms that endeavor to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates and also it is a subset of machine learning and is at the heart of deep learning algorithms.

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1. Why do we need biological neural networks?

  1. To make smart human interactive & user friendly system
  2. To apply heuristic search methods to find solutions of problem
  3. To solve tasks like machine vision & natural language processing
  4. All of the above

Answer : D
Explanation: To make smart human interactive & user friendly system, to apply heuristic search methods to find solutions of problem, to solve tasks like machine vision & natural language processing are the basic aims that a neural network achieve.

2. Artificial neural network is used for

  1. Classification
  2. Clustering
  3. Pattern recognition
  4. All of the above

Answer : D
Explanation: Artificial neural network is used for: Classification, Clustering and Pattern recognition all of the above.

3. Artificial Neural Network is based on which approach?

  1. Weak Artificial Intelligence approach
  2. Cognitive Artificial Intelligence approach
  3. Strong Artificial Intelligence approach
  4. Applied Artificial Intelligence approach

Answer : B
Explanation: Artificial Neural Network is based on Cognitive Artificial Intelligence approach. So, option B is correct.

4. A Neural Network can answer

  1. For Loop questions
  2. what-if questions
  3. IF-The-Else Analysis Questions
  4. None of the mentioned

Answer : B
Explanation: A Neural Network can answer what-if questions. So, option B is correct.

5. The first neural network computer:

  1. AM
  2. AN
  3. RFD
  4. SNARC

Answer : D
Explanation: SNARC is the first neural network computer. So, option D is correct.

6. ________ computes the output volume by computing dot product between all filters and image patch

  1. Input Layer
  2. Convolution Layer
  3. Pool Layer
  4. Activation Function Layer

Answer : B
Explanation: Convolution Layer computes the output volume by computing dot product between all filters and image patch.

7. _____ is/are the ways to represent uncertainty

  1. Fuzzy logic
  2. Entropy
  3. Probability
  4. All of the above

Answer : D
Explanation: All of the above

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8. What is Adaline in neural networks?

  1. Adaptive line element
  2. Automatic linear element
  3. Adaptive linear element
  4. None of the above

Answer : C
Explanation: In neural networks, adaline is adaptive linear element.

9. Who was the inventor of the first neurocomputer?

  1. Dr. Robert Hecht-Nielsen
  2. Dr. John Hecht-Nielsen
  3. Dr. Alex Hecht-Nielsen
  4. Dr. Steve Hecht-Nielsen

Answer : A
Explanation: Dr. Robert Hecht-Nielsen was the inventor of the first neurocomputer.

10. In which ANN, loops are allowed?

  1. FeedForward ANN
  2. ForwardFeed ANN
  3. FeedBack ANN
  4. None of the above

Answer : C
Explanation: In FeedBack ANN, loops are allowed. They are used in content addressable memories. So, option C is correct.

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