Computer Science homework help.
1. What are the 3 characteristics of Big Data, and main considerations in processing Big Data.
2. Explain the Differences b/w Business Intelligence And Data Science.
3. What are 4 classifications of Big data Structures.
4. Describe each phase in Data Analytics LifeCycle.
5. Which Phase would take more time and less time (in reference to question 4)
6. What is command to create scatterplot for data frame df, assuming values for x and y.
7. What is rug plot ?
8. Type I and Type II error, Why is other more serious than other.
9. Why consider K-means clustering unsupervised?
10. What are the steps in the K-means clustering Algorithm ?
11. What are 3 popular cases of the Rules mining algorithm?
12. Define Support and Confidence in Data Science & Big Data Analyst?
13. How do you “Hold-out” data set to evaluate the effectiveness of the rules generated?
14. What are use cases of linear regression models.
15. Compare and contrast linear and logistic regression methods.
2. Explain the Differences b/w Business Intelligence And Data Science.
3. What are 4 classifications of Big data Structures.
4. Describe each phase in Data Analytics LifeCycle.
5. Which Phase would take more time and less time (in reference to question 4)
6. What is command to create scatterplot for data frame df, assuming values for x and y.
7. What is rug plot ?
8. Type I and Type II error, Why is other more serious than other.
9. Why consider K-means clustering unsupervised?
10. What are the steps in the K-means clustering Algorithm ?
11. What are 3 popular cases of the Rules mining algorithm?
12. Define Support and Confidence in Data Science & Big Data Analyst?
13. How do you “Hold-out” data set to evaluate the effectiveness of the rules generated?
14. What are use cases of linear regression models.
15. Compare and contrast linear and logistic regression methods.
