Chapter 12: Realizing Business Value with AutoML

You have acquired a wide variety of technical skills throughout this book. You're now able to train regression, classification, and forecasting models with AutoML. You can code AutoML solutions in Python using Jupyter notebooks, you know how to navigate Azure Machine Learning Studio, and you can even integrate machine learning pipelines in Azure Data Factory (ADF). Yet, technical skills alone will not guarantee the success of your projects. In order to realize business value, you have to gain the trust and acceptance of your end users. 

In this chapter, you will begin by learning how to present end-to-end architectures in a way that makes it easy for end users to understand. Then, you will learn which visualizations and metrics to use to show off your model's performance, after which you will learn how to visualize and interpret AutoML's built-in explainability function.

You will also explore options to run...