Summary

This chapter wraps up all of the concepts and techniques that are required to successfully train a machine learning model based on training data. In this chapter, we introduced the idea of building a comprehensive machine learning program that not only accounts for the stages involved in the preparation of the dataset and creation of the ideal model, but also the stage related to making the model accessible for future use, which is accomplished by carrying out three main processes: saving the model, loading the model, and creating a channel that allows users to easily interact with the model and obtain an outcome. The pickle module was also introduced in this regard.

Further, to make the model accessible to users, the ideal channel (for example, an API, an application, a website or a form) needs to be selected according to the type of user that will interact with the model. Then, an intermediary needs to be programmed, which can connect the channel with the model. This intermediary...