Machine Learning MCQ : Test 10

Explore this diverse selection of multiple-choice questions (MCQs) designed for various examinations. Machine Learning MCQ : Test 10 focuses on essential aspects of the subject, ensuring comprehensive preparation across different categories and fields of study to enhance your knowledge and readiness. The right answers for each question is provided next to respective questions for your convenience, you can either attend the test or dirtectly access the right answers by clicking the show correct answer button.

Each correct answer earns 1 mark, while each incorrect answer deducts 0.3 marks.

1. Which algorithm is used for hierarchical clustering?

2. How does dropout prevent overfitting in neural networks?

3. Which evaluation metric is used for regression problems?

4. What is the purpose of using a Gaussian mixture model (GMM)?

5. How does the BERT model improve NLP tasks?

6. Which method is used for dimensionality reduction in sparse data?

7. What is the role of an optimizer in neural networks?

8. Which algorithm is commonly used for collaborative filtering?

9. How does a variational autoencoder (VAE) differ from a traditional autoencoder?

10. Which method is used for text generation in NLP?

11. How does a Siamese network work?

12. Which evaluation metric is used for ranking problems?

13. What is the main challenge in training a GAN?

14. Which method is used for speech recognition?

15. How does the Transformer architecture differ from RNNs?

16. What is the purpose of a reinforcement learning agent's policy?

17. Which method is used to handle high cardinality categorical features?

18. How does the gradient clipping technique help in training RNNs?

19. What is the main advantage of using a capsule network?

20. Which algorithm is used for outlier detection?

21. How does an attention mechanism improve sequence modeling?

22. Which method is used for dimensionality reduction in high-dimensional data?

23. What is the main purpose of using a variational autoencoder (VAE)?

24. How does a reinforcement learning agent learn?

25. Which algorithm is used for hierarchical clustering?

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