Chapter 7. Guiding an AI project to success
- Performing sensitivity analysis on the ML pipeline
- Assessing advanced sensitivity analysis methods
- Accounting for the effects of time in your pipeline
- Organizing a project so that “If you fail, you fail fast”
This chapter answers the questions: “What should I do when my ML pipeline needs improvement, and how do I know that I’m improving the right stage of the ML pipeline?” Such issues almost always arise for an AI product that’s already on the market, and your goal is to continue to improve an AI product’s user experience.
The same questions arise during the initial development of the AI project when your current ML pipeline needs to improve to meet business goals. Technically, this situation happens when the Min part of MinMax analysis is failing, and the Max part is passing. (Section 6.4.3 describes details of such a scenario.)
In this chapter, I’ll show you how to improve your ML pipeline. The key is to correctly decide the stage of an ML pipeline on which you should concentrate your improvement efforts, which allows you to economize your resources. The Economize part of the CLUE process addresses how to best direct your resources.