Summary

Gaining end user acceptance can be difficult, but having the right approach can make it a lot easier. Walking your end users through an architectural diagram, carefully explaining the model's performance to them using the right metrics, and spending time explaining which features the model is using to make predictions are all key to selling your solution to end users. Furthermore, you can tailor your message based on what type of solution you are building to gain end user trust.

You are now at the end of the book and I'd like you to reflect on the journey. You've acquired many technical skills, including the ability to train AutoML models, deploy AutoML models for scoring in batch and real-time scoring, and design, create, and implement full end-to-end AutoML solutions. You also have an approach to sell those solutions to your business partners, gain their trust, and, ultimately, realize value. By crafting powerful solutions with AutoML on Azure, you&apos...