In the last section, we spent a lot of time discussing machine learning models and how they correspond to frameworks for medical decision making. But how does one actually train a machine learning model? In healthcare, machine learning usually consists of a pattern of stereotyped tasks. We can refer to the collection of these tasks as a pipeline. While no two pipelines are exactly the same for any two machine learning applications, pipelines allow us to describe the machine learning process. In this section, we describe a generalized pipeline that many simple machine learning projects tend to follow, particularly when dealing with structured data, or data that can be organized into rows and columns.