Welcome to the Vector Database Cloud Tutorials repository! This repository offers a collection of step-by-step guides, educational content, and curated links to high-quality open-source tutorials. Whether you're a beginner or an advanced user, you'll find valuable resources to enhance your understanding of vector databases like pgvector, Milvus, Qdrant, and ChromaDB.
This repository is a hub for tutorials, including original content and curated links to external resources. The aim is to provide comprehensive learning paths for understanding and utilizing vector databases in various applications, from basic setup to advanced integrations and optimizations.
- Basic understanding of databases and data structures
- Familiarity with Python programming
- Knowledge of machine learning concepts (for advanced tutorials)
- Access to vector database systems (e.g., pgvector, Milvus, Qdrant, ChromaDB)
- Introduction to Vector Databases: An overview of vector databases and their applications.
- Setting Up pgvector: Step-by-step guide for installing and configuring pgvector.
- Basic Operations with Milvus: Learn how to perform basic operations with Milvus.
- Optimizing Vector Searches: Techniques for enhancing the performance of vector searches.
- Integrating Vector Databases with Machine Learning Models: How to use vector databases with popular machine learning frameworks.
- Scalability and Performance Tuning: Best practices for scaling vector databases.
Below are curated links to external tutorials and resources. These are high-quality, open-source materials that provide in-depth knowledge:
- Hugging Face Course on Transformers: A comprehensive course on transformer models, which can be integrated with vector databases for enhanced NLP applications.
- Milvus Documentation: Official Milvus documentation, including tutorials on deploying and managing Milvus.
- Vector Search with FAISS: An introduction to FAISS, a library for efficient similarity search and clustering of dense vectors, which can be used alongside vector databases.
Feel free to explore these resources and expand your knowledge of vector databases!
To use these tutorials:
- Clone this repository to your local machine.
- Navigate to the specific tutorial you're interested in.
- Follow the instructions provided in the tutorial's README or markdown file.
- For external resources, follow the links provided and adhere to their respective usage guidelines.
We welcome contributions from the community! If you have developed a tutorial or found a valuable external resource, please follow these steps:
- Fork the repository.
- Create a new branch for your contribution.
- Add your tutorial or resource. For tutorials, include all necessary files, such as code samples and documentation.
- Submit a pull request with a clear description of your contribution.
Please ensure you provide clear, well-documented tutorials with practical examples. If linking to external tutorials, ensure proper attribution and check for license compatibility.
For any issues or suggestions, please use the issue tracker.
We adhere to the Vector Database Cloud Code of Conduct. Please respect these guidelines when contributing to or using this repository.
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Copyright (c) 2024 Vector Database Cloud
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially
Under the following terms:
- Attribution — You must give appropriate credit to Vector Database Cloud, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests Vector Database Cloud endorses you or your use.
Additionally, we require that any use of this guide includes visible attribution to Vector Database Cloud. This attribution should be in the form of "Tutorials created by Vector Database Cloud" or "Based on Vector Database Cloud tutorials", along with a link to https://vectordbcloud.com, in any public-facing applications, documentation, or redistributions of this guide.
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For the full license text, visit: https://creativecommons.org/licenses/by/4.0/legalcode
The information and resources provided in this community repository are for general informational purposes only. While we strive to keep the information up-to-date and correct, we make no representations or warranties of any kind, express or implied, about the completeness, accuracy, reliability, suitability or availability with respect to the information, products, services, or related graphics contained in this repository for any purpose. Any reliance you place on such information is therefore strictly at your own risk.
Vector Database Cloud configurations may vary, and it's essential to consult the official documentation before implementing any solutions or suggestions found in this community repository. Always follow best practices for security and performance when working with databases and cloud services.
The content in this repository may change without notice. Users are responsible for ensuring they are using the most current version of any information or code provided.
This disclaimer applies to Vector Database Cloud, its contributors, and any third parties involved in creating, producing, or delivering the content in this repository.
The use of any information or code in this repository may carry inherent risks, including but not limited to data loss, system failures, or security vulnerabilities. Users should thoroughly test and validate any implementations in a safe environment before deploying to production systems.
For complex implementations or critical systems, we strongly recommend seeking advice from qualified professionals or consulting services.
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