Summary
In this chapter, you were given an overview of the various tools that can help you understand your models. You started with the Interpret-Community package, which allows you to understand why the model is making its predictions. You learned about the various interpretation techniques and explored the explanation dashboard, which provides views such as feature importance. You then saw the error analysis dashboard, which allows you to determine where the model is performing poorly. Finally, you learned about the fairness evaluation techniques, the corresponding dashboard that enables you to explore potentially unfair results, and the methods you can use to mitigate potential fairness issues.
In the next chapter, you will learn about Azure Machine Learning pipelines, which allow you to orchestrate model training and model results interpretation in a repeatable manner.
