Machine Learning Engineering in Action

6 Experimentation in action: Testing and evaluating a project

This chapter covers

• Evaluating potential approaches for an ML project
• Objectively selecting an approach for a project’s implementation

The preceding chapter covered all the preparatory actions that should be taken to minimize the risks associated with an experimentation phase of a project. These range from conducting research that informs the options available for solving the problem to building useful functions that the team members can leverage during the prototyping phase. We will continue the previous scenario throughout this chapter, a time-series modeling project for airport passenger demand forecasting, while focusing on methodologies to be applied to experimental testing ...