Summary
In this chapter, we covered the seven popular XAI frameworks that are available in Python: the DALEX, Explainerdashboard, InterpretML, ALIBI, DiCE, ELI5, and H2O AutoML explainers. We have discussed the supported explanation methods for each of the frameworks, the practical application of each, and the various pros and cons. So, we did cover a lot in this chapter! I also provided a quick comparison guide to help you decide which framework you should go for. This also brings us to the end of Part 2 of this book, which gave you practical exposure to using XAI Python frameworks for problem-solving.
Section 3 of this book is targeted mainly at the researchers and experts who share the same passion as I do: bringing AI closer to end users. So, in the next chapter, we will discuss the best practices of XAI that are recommended for designing human-friendly AI systems.