patchy631/ai-engineering-hub resource

Health v2 · maintenance only

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37186 stars · 6144 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A curated collection of 90+ production-ready tutorial projects on LLMs, RAG, AI agents, and MCP, organized by difficulty from beginner to advanced. Each project is a hands-on Jupyter Notebook example that can be implemented, adapted, and scaled in real applications.

Use cases

• learn how to build RAG applications
• find example AI agent projects to adapt
• get started with LLM engineering as a beginner
• build a local OCR app with vision models
• learn MCP with real-world projects
• study fine-tuning and production AI systems
• follow an AI engineering learning roadmap

When to choose

• you want hands-on, runnable notebook examples for LLM, RAG, and agent patterns
• you need projects sorted by skill level from beginner to advanced
• you want MIT-licensed code you can freely adapt into your own apps

When to avoid

• you need a production-grade library or framework rather than tutorials
• you want a single maintained tool with API stability guarantees
• you need non-Python or non-LLM AI engineering resources

Facets

learning-resource · maturity active

rag agent-framework llm-inference mcp ocr chatbot prompt-engineering large-language-models artificial-intelligence tutorials machine-learning python cross-platform jupyter-notebooks tutorials example-projects llm-apps hands-on-learning streamlit ai-agents retrieval-augmented-generation natural-language-processing

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markdown · JSON · MCP: product_card(name="patchy631/ai-engineering-hub")