The machine learning process

A typical data analytics and data science process involves gathering raw data, cleaning data, consolidating data, and integrating data. Following this, we apply statistical and machine learning techniques to the preprocessed data in order to generate a machine learning model and, finally, summarize and communicate the results of the process to business stakeholders in the form of data products. A high-level overview of the machine learning process is presented in the following diagram:

Figure 6.1 – The data analytics and data science process

As you can see from the preceding diagram, the actual machine learning process itself is just a small portion of the entire data analytics process. Data teams spend a good amount of time curating and preprocessing data, and just a portion of that time is devoted to building actual machine learning models.

The actual machine learning process involves stages that allow you to carry out...