Creating a Language Understanding Model Using Azure Language Service

Azure AI Service for Language is a cloud-based service that provides advanced natural language processing over raw text and includes four main functions: sentiment analysis, key phrase extraction, language detection, and entity recognition. Language understanding is one of the services that can be used to create a custom language model that can train and deploy a bot.

Organizations use custom language models to provide a more natural interaction with their bots. It helps organizations create a model that is specific to their domain and can be used to serve their customers better.

In this hands-on lab, you will be working with Azure Language Studio to create a custom language model along with custom entities and intents. You will also train and deploy the model to test the functionality of Language Services.

Learning objectives

Upon completion of this advanced-level lab, you will be able to:

• Create a custom language model project
• Create custom entities and intents
• Map entities to intents
• Train and deploy the model
• Test the language model

Intended audience

• Candidates for Azure AI Engineer Associate certification (AI-102)
• Cloud Architects
• DevOps Engineers
• Machine Learning Engineers

Prerequisites

Familiarity with the following will be beneficial but is not required:

• Azure AI Services
• Azure Language Studio

The following content can be used to fulfill the prerequisites:

• Exploring Azure Question Answering Service
• Exploring Azure Computer Vision Solution and Vision Studio