Azure AI Search is a powerful search engine with comprehensive search capabilities, largely due to its support for vector search. Vector search offers many useful features, enabling search across various types of unstructured data. This represents a significant departure from traditional search methodologies, which typically rely on exact matches for data retrieval.
Azure AI Search also provides extensive configuration options through multiple access points. When combined with the Azure OpenAI service, it becomes an even more capable search system.
In this lesson, you’ve learned how to:
Configure vector search capabilities in Azure AI Search.
Generate and store embeddings for efficient semantic search.
Implement a basic vector search query using Azure AI Search.
In the next lesson, you’ll learn and practice an even more advanced form of search using Azure AI Search.
See forum comments
This content was released on Nov 15 2024. The official support period is 6-months
from this date.
Azure AI Search redefines search with semantic precision through powerful vector capabilities.
Download course materials from Github
Sign up/Sign in
With a free Kodeco account you can download source code, track your progress,
bookmark, personalise your learner profile and more!
Previous: Demo 02
Next: Lesson 2: Vector Search in Azure AI Search
All videos. All books.
One low price.
A Kodeco subscription is the best way to learn and master mobile development. Learn iOS, Swift, Android, Kotlin, Flutter and Dart development and unlock our massive catalog of 50+ books and 4,000+ videos.