CA-305 Big data (BBACA) || Question Bank

CA-305 Big data (BBACA) || Question Bank

1. What is Big Data? 

2. Explain the characteristics of Big Data. 

3. Explain the types of Big Data. 

4. Explain the application of Big Data in E-commerce.

5. What is Data Science?  

6. Explain statistical inferences. 

7. Explain population and types of population. 

8. Differentiate between population and sample. 

9. What is correlation? What are the possible results of correlation?

10. What is probability? Explain its types.  

11. Explain the types of regression in brief.

12. What is Machine Learning? 

13. Explain the five applications of Machine Learning Explain the steps in Machine Learning life cycle. 

14. What is Supervised Learning? 

15. What is K-nearest neighbour algorithm? 

16. How Naive Bayes algorithm works?

17. Explain Decision Tree algorithm in detail. 

18. Explain SVM algorithm in detail. 

19.  What are the drawbacks of the Linear Model?

20. What is Linear Regression? 

21. What is the difference between Regression and Classification Machine Learning techniques? 

22. What is Unsupervised learning?

23. Explain the types of cluster analysis. 

24. Explain steps of EM algorithm with example. 

25. Explain types of regression analysis in brief.

26. What is R? 

27. What are the data structures in R? 

28. Explain general format of Matrices in R. 

29. How do you assign a variable in R? Explain with example. 

30. Explain the steps to classify the data in WEKA. 

31. Explain Arff file format. 

32. Explain test options of classify.

Big data imp questions for exam