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.

For saving and loading a model, the pickle module was introduced. This module is capable of serializing the model to save it in a file, while also being capable of deserializing it to make use of the model in the future.

Furthermore, to make the model accessible to users, the ideal channel (for example, an API, an application, a website, or a form) needs to...