Summary
In this chapter, we discussed the various configurations of the Personalizer Cognitive Service and some examples of where Personalizer can be used to benefit your organization. Rank and reward configurations will help you to better provide the most relevant options to your users, and with the exploration capability, you can offer less popular choices if they happen to be the best. We also discussed the various machine learning algorithms that are used to help with Reinforcement Learning, to improve the deployed machine learning models built for Personalizer. Finally, we were able to provide an end-to-end solution to customize how items will be ranked and rewarded. Using this logic, you can leverage an API with a simple web interface or Power Apps deployed to your organization, or embed the logic into an existing application to offer better suggestions.
In the next chapter, we will look at how you can improve your customer service team with the Azure Speech service.
