Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language. You can use the Language Understanding service to build language models for your applications.
Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language. You can use the Language Understanding service to build language models for your applications.
Who Should Attend?
- Database Professional
- Microsoft Professional
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Prerequisites
Before starting this learning path, you should already have:
- Familiarity with Azure and the Azure portal.
- Experience programming with C# or Python. If you have no previous programming experience, we recommend you complete the Take your first steps with C# or Take your first steps with Python learning path before starting this one.
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Outline
Module 1: Analyze text with Azure AI Language
- Detect language from text
- Analyze text sentiment
- Extract key phrases, entities, and linked entities
Module 2: Create question answering solutions with Azure AI Language
- Understand question answering and how it compares to language understanding.
- Create, test, publish, and consume a knowledge base.
- Implement multi-turn conversation and active learning.
- Create a question answering bot to interact with using natural language.
Module 3: Build a conversational language understanding model
- Provision Azure resources for Azure AI Language resource
- Define intents, utterances, and entities
- Use patterns to differentiate similar utterances
- Use pre-built entity components
- Train, test, publish, and review an Azure AI Language model
Module 4: Create a custom text classification solution
- Understand types of classification projects
- Build a custom text classification project
- Tag data, train, and deploy a model
- Submit classification tasks from your own app
Module 5: Custom named entity recognition
- Understand tagging entities in extraction projects
- Understand how to build entity recognition projects
Module 6: Translate text with Azure AI Translator service
- Provision a Translator resource
- Understand language detection, translation, and transliteration
- Specify translation options
- Define custom translations
Module 7: Create speech-enabled apps with Azure AI services
- Provision an Azure resource for the Azure AI Speech service
- Use the Azure AI Speech to text API to implement speech recognition
- Use the Text to speech API to implement speech synthesis
- Configure audio format and voices
- Use Speech Synthesis Markup Language (SSML)
Module 8: Translate speech with the Azure AI Speech service
- Provision Azure resources for speech translation.
- Generate text translation from speech.
- Synthesize spoken translations.
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