# docs-notebooks

**Repository Path**: mirrors_mongodb/docs-notebooks

## Basic Information

- **Project Name**: docs-notebooks
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-11-02
- **Last Updated**: 2025-02-23

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# MongoDB Documentation Notebooks

This repository contains Jupyter Notebooks that follow
tutorials and code examples in MongoDB's official [Atlas Vector Search documentation](https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-overview/). You can run, download, and modify these notebooks as you learn how to use MongoDB Atlas Vector Search for your use case.

## Overview

Each notebook corresponds to a page or example in our documentation.
Refer to the docs page linked in each notebook for prerequisites, set-up instructions, and detailed explanations of the code.

The following table summarizes the contents of the notebooks in each directory:

| Directory          | Description                                      |
|--------------------|--------------------------------------------------|
| [/create-embeddings](https://github.com/mongodb/docs-notebooks/tree/main/create-embeddings) | Learn how to generate embeddings for vector search |
| [/get-started](https://github.com/mongodb/docs-notebooks/tree/main/get-started) | Complete our quick start tutorial |
| [/ai-integrations](https://github.com/mongodb/docs-notebooks/tree/main/ai-integrations) | Implement RAG with popular AI frameworks that integrate with MongoDB |
| [/manage-indexes](https://github.com/mongodb/docs-notebooks/tree/main/manage-indexes) | Create, view, edit, and delete vector search indexes |
| [/quantization](https://github.com/mongodb/docs-notebooks/tree/main/quantization) | Quantize your vector embeddings for efficient processing |
| [/run-queries](https://github.com/mongodb/docs-notebooks/tree/main/run-queries) | Learn how to run vector search queries (ANN and ENN) |
| [/use-cases](https://github.com/mongodb/docs-notebooks/tree/main/use-cases) | Implement RAG using a MongoDB-native retrieval system |

## Other Resources

- [MongoDB Official Documentation](https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-overview/)
- [Generative AI Use Cases Repository](https://github.com/mongodb-developer/GenAI-Showcase/tree/main)

## License

This project is licensed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0).

## Issues

To report an issue with any of these notebooks, please leave feedback through
the corresponding documentation page linked at the top of the file. Using the
`Rate This Page` button, you can add a comment about the issue after leaving
a star rating.

## Contributing

We are not currently accepting public contributions to this repository at this
time.