Kai R. Larsen and Daniel S. Becker
- Published in print:
- 2021
- Published Online:
- July 2021
- ISBN:
- 9780190941659
- eISBN:
- 9780197601495
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780190941659.003.0002
- Subject:
- Business and Management, Information Technology, Innovation
This section covers the first steps of a the Machine Learning Life Cycle Model; how to specify a business problem, acquire subject matter expertise, define prediction target, define unit of analysis, ...
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This section covers the first steps of a the Machine Learning Life Cycle Model; how to specify a business problem, acquire subject matter expertise, define prediction target, define unit of analysis, identify success criteria, evaluate risks, and finally, decide whether to continue a project. Focus is on who will use the model, whether management is supportive, whether the drivers of the model can be visualized, and how much value a model can produce.Less
This section covers the first steps of a the Machine Learning Life Cycle Model; how to specify a business problem, acquire subject matter expertise, define prediction target, define unit of analysis, identify success criteria, evaluate risks, and finally, decide whether to continue a project. Focus is on who will use the model, whether management is supportive, whether the drivers of the model can be visualized, and how much value a model can produce.
