Machine Learning Engineering in Action

5 Experimentation in action: Planning and researching an ML project

This chapter covers

• The details of a project’s research phase
• The process and methodology of conducting solution experimentation for a project

We spent the preceding two chapters focusing on the processes surrounding planning, scoping of work, and communication among a team working on an ML project. This chapter and the next two focus on the next most critical aspects of ML work as it pertains to data scientists: research, experimentation, prototyping, and MVP development.

Once a project’s requirements have been thoroughly captured from planning meetings (as much as can be realistically achieved) and the goal of the modeling solution has been defined, the next phase of creating ...