This chapter covers
This chapter picks up where chapter 7 left off. Now that you know how to use the Framing Canvas to create an ML-friendly vision for your project, it’s time to put together the other ingredients that you need. Bringing a project to life requires three main ingredients: the ML model, data, and people. While choosing a good ML model is a task for the technical team, it’s your job to recruit them and craft a data strategy so they can get to work. This chapter focuses on how to find and manage data, and how to recruit a team of talented people with the right skills for your project.
One of our goals when writing this book was to make you think critically about data and understand how engineers use it to build ML models. Because data is so crucial, developing a coherent data strategy is critical for the success of any project. In part 1, we talked about data in a way that took for granted that you had it readily available to build your models. You can probably guess that this is rarely the case; this chapter will fill in the gaps and help you understand how much data you need, where you can get it, and how to manage it.