chapter four
4 Before you model: Communication and Logistics of projects
This chapter covers
- Communication strategies and techniques for ensuring that the early stages of an ML project (from planning to prototype of a solution) capture the elements that actually solve a business problem
- Determining how to interact with a larger team throughout development to gain feedback and make adjustments through the use of phased planned meetings that focus on relatable demonstrations of the in-progress version of a solution
- Why setting limits on research, experimentation, and prototyping are important, as well as how to define what they should be so that you can actually ship your project to production eventually
- Reasons why and how to incorporate business rules and restrictions on ML projects to ensure that a code base is flexible to adapt to last-minute unexpected changes that need to be made
- How to communicate effectively to a non-technical audience and how to explain what your model can and can’t do to reduce the friction of complex projects and ensure that meetings are shorter and more efficient