English | Size: 943.64 MB
Genre: eLearning
Description
This learning path will give you in-depth tutorials on adding artificial intelligence to your customer-facing applications. I’ve chosen two of the most common ways that companies add artificial intelligence to their customer interactions.
First, if you have a help desk, then there are probably a handful of questions that get asked much more frequently than others. If you could automate the responses to those questions, it would not only reduce your costs, but it would also let your help desk personnel focus on the more complex questions.
You will learn how to:
Create a chatbot that can answer support questions about particular products or services
Combine Azure Bot Service and Azure QnA Maker to do this
Add speech input and output capabilities to a chatbot
The second use case is even more common. If your organization sells products, or even if it offers free items, such as news articles, then you can increase sales or customer engagement by adding recommendations for other items that your customers might want. Even if you already have a recommendation system, it might be possible to get better recommendations by building a more finely tuned model, which I’ll show you how to do.
You will learn how to:
Implement the Microsoft Product Recommendations Solution on Azure
Deploy and test the solution
Fine-tune a recommendation model
Evaluate the effectiveness of different models
Make API calls to the recommendation system
Create and configure an Azure QnA Maker knowledge base
Create an Azure Bot Service chatbot that answers questions
Deploy a recommendation engine on Azure
Test and evaluate different recommendation models
Make API calls to the Microsoft Product Recommendations Solutions
People who are interested in artificial intelligence services on Azure, especially chatbots and recommendation engines
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