Module 2 - Data Mining and Visualization

Question 1

Which are the two frameworks which describe ML solutions?

Answer 1

• Descriptive, Diagnostic, Predictive, Prescriptive

- Classification, Regression, Clustering, Association

Question 2

Which of the ML learning techniques are supervised and what does it mean?

Answer 2

Classification, Regression

The algorithm is trained with labeled data

Question 3

What’s to prefer if choosing between more and better data or a more sophisticated algorithm?

Answer 3

More and better data generally beats more sophisticated algorithms

Question 4

Explain the “Toyota-way” to determine bottlenecks in short.

Answer 4

Two binary machine states, active and not active. Detect the bottleneck by simply detecting which machine has the longest active time period

Question 5

Name another aspect than high active periods which can indicate a bottleneck?

Answer 5

Unique machine behavior

Question 6

What does skewness in measures of shape refer to?

Answer 6

Refers to the distortion or asymmetry in a normal distribution§

Question 7

How much skew does a normal distribution have?

Answer 7

Zero

Question 8

What does positively skewed data mean?

Answer 8

Mean greater than median

Question 9

How would you describe a cluster analysis?

Answer 9

A technique to find patterns in unclassified data, by making clusters with objects that are similar to each other but different from objects in other clusters.

Question 10

What is the role of a data producer?

Answer 10

Generate data

Must understand why the data is collected

Question 11

What is the role of a data user?

Answer 11

Use and create relevance out of data

Question 12

What is the role of a data custodian?

Answer 12

Store and maintain data, responsible for its security as well