Introduction
Welcome to the Introduction to Vector Search lab!
Lab goalsâ
Learn how to build vector search on MongoDB Atlas
What you'll learnâ
- What is vector search
- What are embeddings
- How to store embeddings along with MongoDB documents
- How to create a vector search index
- How to run vector queries
- How to optimize vector search
- Different search methods in MongoDB and hybrid approaches
Time to completeâ
120 mins
Navigation bar iconsâ
In the navigation bar and in some pages, you will notice some icons. Here is their meaning:
| Icon | Meaning | Description |
|---|---|---|
| đ | Lecture material | If you are following along in an instructor-led session, they probably have covered this already. |
| đ | Hands-on content | Get ready to do some hands-on work. You should follow these steps. |
| đ | Documentation | Reference documentation for hands-on portions of the lab. |
| đŠč | Advanced content | This content isn't covered during the lab, but if you're interested in learning more, you can check it out. |