I need help with a Computer Science question. All explanations and answers will be used to help me learn.

Question 1

What are the three chracteristicts of Big Data, and what are the main considerations in processing big data?

Question 2

Explain the differences between BI and Data Science

Question 3

Briefly describe each of the four classifications of Big Data Structure types (i.e Structured to Unstructured).

Question 4

List and briefly describe each of the phases in the Data Analytics LifeCycle.

Question 5

In which phase would the team expect to invest most of the project time?Why? Where would the team expect to spend the least time?

Question 6

Which R command would create a scatterplot for the dataframe “df”, assuming df contains values for x and y?

Question 7

What is a rug plot used for in a density plot?

Question 8

What is a type1 error? What is a type 2 error? Is one always more serious than the other? Why?

Question 9

Why do we consider K-means clustering as a unsupervised machine learning algorithm?

Question 10

Detail the four steps in the K-means clustering algorithm.

Question 11

List three popular use cases of the Association Rules mining algorithms?

Question 12

Define Support and Confidence

Question 13

How do you use a “hold-out” dataset to evaluate the effectiveness of the rules generated?

Question 14

List two use cases of linear regression models

Question 15

Compare and contrast linear and logistic regression methods

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