Technical requirements
The primary goal of this chapter is to provide a conceptual understanding of the model explainability methods. However, I will provide certain tutorial examples to implement some of these methods in Python on certain interesting datasets. We will be using Python Jupyter notebooks to run the code and visualize the output throughout this book. The code and dataset resources for Chapter 2 can be downloaded or cloned from the following GitHub repository: https://github.com/PacktPublishing/Applied-Machine-Learning-Explainability-Techniques/tree/main/Chapter02. Other important Python frameworks that are required to run the code will be mentioned in the notebooks along with other relevant details to understand the code implementations within these concepts.