Chapter 5: Model Evaluation and Packaging

In this chapter, we will learn in detail about ML model evaluation and interpretability metrics. This will enable us to have a comprehensive understanding of the performance of ML models after training them. We will also learn how to package the models and deploy them for further use (such as in production systems). We will study in detail how we evaluated and packaged the models in the previous chapter and explore new ways of evaluating and explaining the models to ensure a comprehensive understanding of the trained models and their potential usability in production systems.

We begin this chapter by learning various ways of measuring, evaluating, and interpreting the model's performance. We look at multiple ways of testing the models for production and packaging ML models for production and inference. An in-depth study of the ML models' evaluation will be carried out as you will be presented with a framework to assess any kind...