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Table of Contents
Part I: Introducing Machine Learning: Past and Present
The Historical Lens of Sub-Fields
The State of the People Data Industry
Part II: The Science, Philosophy, and Legality of using Machine Learning with People Data
Scientific Considerations when Working with Behavioral Data
Legal and Ethical Considerations when Working with Employee Data
Part III:
Instruction and Application of Machine Learning in an Employee Data Context
Introduction and Overview of Stats and Computing
Interpret and communicate
Data Analyzing
Data Wrangling.
The Historical Lens of Sub-Fields
The State of the People Data Industry
Part II: The Science, Philosophy, and Legality of using Machine Learning with People Data
Scientific Considerations when Working with Behavioral Data
Legal and Ethical Considerations when Working with Employee Data
Part III:
Instruction and Application of Machine Learning in an Employee Data Context
Introduction and Overview of Stats and Computing
Interpret and communicate
Data Analyzing
Data Wrangling.