Personalized AI at scale with Vector Databases on Azure CosmosDB
In this video, you will learn how to inject and use your data in AI using vector databases. I explore converting documents into embeddings and storing them in Azure Cosmos DB, explaining each step along the way. This tutorial covers setting up vector indexes, querying embeddings, and ensuring scalability for your AI systems. Now you can efficiently manage and use your data to make your AI solutions smarter and more accurate!
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Skills you will learn:
1. Converting documents into embeddings
2. Setting up vector indexes in Azure Cosmos DB
3. Querying embeddings using SQL-like syntax
4. Managing large datasets efficiently
5. Enhancing the accuracy and scalability of AI systems
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💭 Code repository used:
https://github.com/Zenulous/ai-with-y...
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