AI Engineering Lab 是一个用于学习和探索人工智能工程相关知识的实验室项目。这是一个沙盒环境,用于实验和理解各种前沿的 AI 技术和概念。
- 学习: 深入理解 AI 工程的核心概念和技术
- 探索: 尝试最新的 AI 技术和工具
- 实验: 通过实际项目巩固理论知识
- 分享: 记录学习过程和经验总结
本项目涵盖以下 AI 工程相关主题:
- 大语言模型 (LLMs): 探索 GPT、Claude、LLaMA 等大型语言模型的应用
- 检索增强生成 (RAG): 实现和优化基于检索的生成系统
- AI 智能体 (Agents): 构建能够自主执行任务的 AI 代理
- 提示工程 (Prompt Engineering): 研究和优化 AI 模型的提示技巧
- 向量数据库: 探索 Pinecone、Weaviate、Chroma 等向量存储解决方案
- AI 工具链: 集成 LangChain、LlamaIndex 等 AI 开发框架
- 模型微调: 学习模型的精细调优和适配技术
ai-engineering-lab/
├── README.md # 项目说明文档
└── ... # 未来将添加更多实验和项目
项目正在建设中,未来将添加各种 AI 工程实验和示例代码。
欢迎提出建议和贡献!如果你有好的想法或发现了问题,请随时:
- 提交 Issue
- 创建 Pull Request
- 分享你的经验和见解
本项目用于学习和研究目的。
AI Engineering Lab is a sandbox project for learning and exploring AI engineering concepts and knowledge. This is an experimental environment for understanding and trying out cutting-edge AI technologies.
- Learn: Deep dive into core AI engineering concepts and technologies
- Explore: Try out the latest AI technologies and tools
- Experiment: Solidify theoretical knowledge through practical projects
- Share: Document learning process and insights
This project covers the following AI engineering topics:
- Large Language Models (LLMs): Exploring applications of GPT, Claude, LLaMA, and other large language models
- Retrieval-Augmented Generation (RAG): Implementing and optimizing retrieval-based generation systems
- AI Agents: Building autonomous AI agents capable of executing tasks
- Prompt Engineering: Researching and optimizing AI model prompting techniques
- Vector Databases: Exploring vector storage solutions like Pinecone, Weaviate, Chroma
- AI Toolchains: Integrating AI development frameworks like LangChain, LlamaIndex
- Model Fine-tuning: Learning model fine-tuning and adaptation techniques
ai-engineering-lab/
├── README.md # Project documentation
└── ... # More experiments and projects coming soon
The project is under construction. Various AI engineering experiments and sample code will be added in the future.
Suggestions and contributions are welcome! If you have good ideas or find issues, feel free to:
- Submit Issues
- Create Pull Requests
- Share your experiences and insights
This project is for learning and research purposes.