Machine Learning MCQs 10

Master Machine Learning MCQS fundamentals with this interactive quiz! The machine learning MCQs test covers supervised learning, neural networks, and recommendation systems.. Test your understanding of key topics like labeled datasets, unsupervised learning, recommender systems, and gradient boosting. Take the Machine Learning MCQs Quiz and level up your skills!

Online Machine Learning MCQs with answers

Online machine learning mcqs with Answers

1. Which approach to machine learning involves rewarding or punishing a computer’s behaviors?

 
 
 
 

2. Recommender systems (e.g., Netflix) use

 
 
 
 

3. A neural network is best suited for

 
 
 
 

4. Unstructured data includes

 
 
 
 

5. In recommendation systems, what term describes the phenomenon of more well-known items being recommended too frequently?

 
 
 
 

6. Supervised machine learning uses labeled datasets to train ————– to classify or predict outcomes

 
 
 
 

7. Content-based filtering is a recommendation system in which recommendations are made based on —————- of the attributes of the content.

 
 
 
 

8. Which is an example of unsupervised learning?

 
 
 
 

9. Structured data refers to

 
 
 
 

10. Which of the following statements correctly describes gradient boosting?

 
 
 
 

11. ML can automate

 
 
 

12. Which term best describes the statement, “a subset of AI that uses computer algorithms to analyze data and make intelligent decisions based on what it has learned without being explicitly programmed”?

 
 
 
 

13. Decision trees are used for

 
 
 
 

14. What are some benefits of boosting?

 
 
 
 

15. Machine learning involves using algorithms and ————— to teach computer systems to analyze and discover patterns in data.

 
 
 
 

16. When several users actively like or dislike content by rating it or giving it a review, this enables ————– filtering.

 
 
 
 

17. Which of the following statements correctly describes gradient boosting?

 
 
 
 

18. What term describes the subclass of machine learning algorithms that offers relevant suggestions to users?

 
 
 
 

19. Supervised learning requires

 
 
 
 

20. What are some benefits of boosting?

 
 
 
 

Question 1 of 20

Online Machine Learning MCQs with Answers

  • Structured data refers to
  • Unstructured data includes
  • Supervised learning requires
  • Which is an example of unsupervised learning?
  • ML can automate
  • Recommender systems (e.g., Netflix) use
  • Decision trees are used for
  • A neural network is best suited for
  • Supervised machine learning uses labeled datasets to train ————– to classify or predict outcomes
  • Machine learning involves using algorithms and ————— to teach computer systems to analyze and discover patterns in data.
  • Which approach to machine learning involves rewarding or punishing a computer’s behaviors?
  • Content-based filtering is a recommendation system in which recommendations are made based on —————- of the attributes of the content.
  • What term describes the subclass of machine learning algorithms that offers relevant suggestions to users?
  • When several users actively like or dislike content by rating it or giving it a review, this enables ————– filtering.
  • In recommendation systems, what term describes the phenomenon of more well-known items being recommended too frequently?
  • What are some benefits of boosting?
  • Which of the following statements correctly describes gradient boosting?
  • What are some benefits of boosting?
  • Which of the following statements correctly describes gradient boosting?
  • Which term best describes the statement, “a subset of AI that uses computer algorithms to analyze data and make intelligent decisions based on what it has learned without being explicitly programmed”?

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