Summary
In summary, you can use conversational language understanding (CLU) to build a model that predicts intents and entities from natural language utterances. A client application can then use this trained model to respond to natural language user input
Two main takeaways from this module are CLU core concepts (utterances, intents, and entities) and how to get started with Azure AI Language's CLU feature. You can use Azure AI Languages's CLU feature to define entities and intents in utterances, and train a language model to predict intents and entities from user input.
You learned you can either use an Azure AI Language resource for authoring and predictions, or an Azure AI services resource to make predictions. Additionally, the exercise taught you how to use the Language Studio web-based interface for creating and managing CLU applications.
Further reading:
- Azure AI Language and CLU documentation.
- What are Azure AI services?
- Get started with Language Studio