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Data Analytics Exam
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Data Analytics Exam
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25 Questions

1. What is bivariate analysis?

2. How to handle continuous attributes in NB?

3. What is the precision of a confusion matrix?

4. Ways to pre-prune a decision tree?

5. What is a correlation coefficient?

6. What is model selection/hyper parameter tuning?

7. What is classification?

8. What is a perfect score using the F measure?

9. What is the broken default loop?

10. Ways to split nominal attributes in a decision tree (2)

11. What is an activation function?

12. What happens when you calculate gradients in ANN?

13. How do we implement an ensemble method?

14. What is the F-measure?

15. What are two types of learning algorithms?

16. Stochastic Gradient Descent

17. Steps in ANN

18. What is a MLP?

19. What are Instance Reduction Algorithms?

20. What are some data quality issues? (4)

21. What is Data Cleaning?

22. ___% of a data scientist's time is spent cleaning the data

23. What are support vectors in an SVM?

24. What are three techniques used for Machine Learning?

25. Con of SVM

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