Description
Overview:
This learning path explores how the Azure AI and Azure Machine Learning Services integrations provided by the Azure AI extension for Azure Database for PostgreSQL – Flexible Server can enable you to build AI-powered apps.
Prerequisites:
Before starting this module, you should have experience working with PostgreSQL databases, writing SQL queries, and a general understanding of AI and ML concepts.
Outline:
1 – Get started with generative AI in Azure Database for PostgreSQL
- Understand generative AI language models
- Describe the Azure AI extension
- Explore the Azure OpenAI schema
- Review the Azure Cognitive schema
- Examine the Azure Machine Learning schema
2 – Enable semantic search in Azure Database for PostgreSQL
- Understand semantic search
- Store vectors in Azure Database for PostgreSQL
- Create embeddings with the Azure AI extension
- Explore semantic search use cases
3 – Summarize data with Azure AI Services and Azure database for PostgreSQL
- Explain extractive summarization
- Explore abstractive summarization
4 – Perform sentiment analysis and opinion mining with Azure Database for PostgreSQL
- Explore sentiment analysis
- Describe opinion mining
5 – Extract insights using Azure AI Language and Azure Database for PostgreSQL
- Extract key phrases
- Recognize entities
- Recognize personally identifiable information (PII) entities
6 – Translate Text with Azure AI Translator and Azure Database for PostgreSQL
- Explore the Azure AI Translator Service
- Translate data in Azure Database for PostgreSQL
7 – Use Azure Machine Learning for inferencing from Azure Database for PostgreSQL
- Explore Azure Machine Learning
- Invoke Azure Machine Learning models
