This is the penultimate chapter of the book. It is about the last phase of the predictive analytics process—model communication and deployment. The point of building a model is using it in some way to solve a problem, so we always need to implement the model; despite this necessity, this stage is often forgotten and overlooked in many courses and resources on machine learning and predictive modeling. This chapter aims to fill this gap.
First, we will talk about the model communication and deployment phase—we will explain the main ways in which we implement a predictive analytics solution—a technical report, a feature of an existing application, or an analytic application. In this section, we talk about some important tips and considerations when communicating the results of a predictive modeling project.
In the following sections...
