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
