A hybrid retrieval system for RAG that combines vector search and graph search, integrating unstructured and structured data. It retrieves context using embeddings and a knowledge graph, then passes it to an LLM for generating accurate responses.
GitHub repository with 55 stars and 6 forks.
Language: Jupyter Notebook
Topics: graph-rag, hybrid-rag, llm, neo4j, rag
Trending score 0.09, freshness score 0.75, stars gained +0, forks gained +0.
2026-11-15: 55 stars and 6 forks.
21 Lessons, Get Started Building with Generative AI
GitHub repository with 123,578 stars and 66,452 forks.
Trending score: 4.21; stars gained: +100; forks gained: +70.
Language: Jupyter Notebook
Topics: ai, azure, chatgpt, dall-e, generative-ai, generativeai
Python - 100天从新手到大师
GitHub repository with 187,853 stars and 55,718 forks.
Trending score: 2.38; stars gained: +22; forks gained: -8.
Language: Jupyter Notebook
AI 课程笔记：langchain / langgraph / python / vibe coding
GitHub repository with 562 stars and 243 forks.
Trending score: 1.16; stars gained: +1; forks gained: +5.
Language: Jupyter Notebook
Topics: agent, agents, ai, atguigu, langchain, langgraph
Learn ML engineering for free in 4 months! Register here 👇🏼
GitHub repository with 14,857 stars and 3,301 forks.
Trending score: 0.00; stars gained: +0; forks gained: +0.
Language: Jupyter Notebook
Topics: course, deployment, docker, fastapi, kubernetes, machine-learning
✅（已完结）超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】
GitHub repository with 24,285 stars and 2,673 forks.
Trending score: 4.30; stars gained: +415; forks gained: +14.
Language: Jupyter Notebook
Topics: book, chinese, computer-vision, deep-learning, machine-learning, natural-language-processing
Build a modern LLM from scratch. Every line commented. Explained like we are five.
GitHub repository with 4,142 stars and 503 forks.
Trending score: 0.00; stars gained: +0; forks gained: +0.
Language: Jupyter Notebook
Topics: attention-mechanism, deep-learning, educational, from-scratch, gpt, language-model