MCQs on Machine Learning (NLP)

This article is a set of  MCQs on Machine Learning (in AI), and it is based on the topic – Natural Language Processing(NLP).

If you missed the previous article of Artificial Intelligence’s previous article, then please click here.

Multiple Choice Questions on Machine Learning

1. What is full form of NLP ?

  1. Neural language processing
  2. Natural Language Processing
  3. both a) and b)
  4. None of the above
Answer: b

2. Natural Language Processing deals with ………………….

  1. the relationship between computer and human (natural) languages.
  2. the relationship between computer and human brain
  3. both a) and b)
  4. None of the above
Answer: a

3. Modern NLP algorithms are based on …………………..

  1. Neural language processing
  2. machine learning
  3. artificial intelligence
  4. all of the above
Answer: b

4. What is aim of NLP?

  1. NLP aims to give computers the ability to do tasks involving human language.
  2. NLP aims to give computers the ability to only reads the human language.
  3. to support artificial intelligence
  4. None of the above
Answer: a

5. It is one of the real world application of NLP.

  1. Topic modeling
  2. Speech Recognition
  3. both a) and b)
  4. none of the above
Answer: c

6. What is the work of POS Tagging?

  1. POS tagging helps to find out the various sentence.
  2. POS tagging helps to find out the various nouns, adverbs, verbs, and map them in a sentence.
  3. name, time, location, date, and other entities present in text.
  4. none of the above
Answer: b

7. what is Text Stigmatization?

Answer: This method uses to compress a text document, creating a summary of major points of documents.

8. It is a example of Text Prediction /Auto-correction?

  1. Gmail and Grammarly
  2. Speech Recognition
  3. both a) and b)
  4. none of the above
Answer: a

9. What is chatbots in NLP?

Answer: The chatbot is Artificial intelligence (AI) software that can emulate a conversation (or a chat) with a user in natural language through applications of messaging, mobile apps, websites, or through the telephones.

10. The below mentioned areas where NLP can be useful –

  1. Automatic Text Summarization
  2. Information Retrieval
  3. Automatic Question-Answering Systems
  4. All of the above
Answer: d

11. It is one of the major challenge’s of NLP Is _________________ .

  1. Handling Tokenization
  2. The Handling Ambiguity of Sentences
  3. Handling POS-Tagging
  4. All of the above
Answer: d

12. Co-reference Resolution is –

  1.  Anaphora Resolution
  2.  Given a sentence or larger chunk of text, determine which words (“mentions”) refer to the same objects (“entities”)
  3.  Both a & b
  4.  None of the above
Answer: b

13.  Solemnization is used for?

  1. To add constant
  2. To Eliminating Universal Quantifiers
  3. For adding the Universal Quantifiers
  4. To Eliminate Existential Quantifiers
Answer: d

14. It is one greatest challenge of NLP in nowadays?

a. Text-to-speech recognization
b. Named Entity Recognition (NER).
c. Both A and B.
d. None of the Above

Answer: b

15. In which ANN, loops are allowed?

a. Soundex
b.  FeedBack
c. FeedForward ANN
d. all of the above

Answer: b

16.What is Natural language processing good for?

a. Summarize blocks of text
b. Automatically generate keyword tags
c. Identify the type of entity extracted
d. All of the above

Answer:d

17. Which 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 mentioned

Answer: d

18. Natural language Processing(NLP) is the field of

a. Artificial Intelligence
b. Computer Science
c. Linguistics
d. All of the above

Answer: b

19. How many types of Artificial Neural Networks?

a. 2
b. 3
c. 4
d. 5

Answer: a

20. basic unit of neural network?

a. neuron
b.  node value
c. Bayes Nets
d. All of the above

Answer: a

In this article, we presented some MCQs on Machine Learning or MCQ questions on machine learning. This helps you in your exams also in various interviews.

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