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Chapter 14 (Thinking Analytically (How to actually solve a problem…
Chapter 14
Thinking Analytically
Data Mining Process
High level data science tasks
How to actually solve a problem
Improve the quality of the target variable
True Positive
True Negative
False positive
False negative
Data is an asset
Privacy issues?
Used for effectiveness of business decisions
How do we even define privacy?
"An embarrassment of meanings"
Privacy in Context
Generalization
Overfitting
General Concepts
Attracting data
Structuring Data
Allows us to decompose problems
Helps us better understand how to solve them
Phone example
Nurturing Data
Competitive Advantage
How to sustain it
Extracting Knowledge from data
Identifying informative attributes
Fitting a model to the data
Choosing a set of parameters
Controlling complexity
Calculating similarities between objects
Classification
Regression
Combinations of humans and computers
Human Creativity/knowledge/common sense
Adds Value
Human interaction
Critical
Optimize objective criteria
Human Judgement
Data represents objective truths
Scientist/phone example
Where can introducing humans add value
Understanding
Creates communication between business stakeholders
Both sides understand it better
Dig into questions
Reveal critical aspects that wouldn't have been uncovered
What is the actual problem?