{"data":{"slug":"patchy631-ai-engineering-hub","name":"ai-engineering-hub","tagline":"Tutorials on LLMs, RAGs, and real-world AI agent applications","github_url":"https://github.com/patchy631/ai-engineering-hub","owner":"patchy631","repo":"ai-engineering-hub","owner_avatar_url":"https://avatars.githubusercontent.com/u/38653995?v=4","primary_language":"Jupyter Notebook","stars":37020,"forks":6107,"topics":["agents","ai","llms","machine-learning","mcp","rag"],"archived":false,"github_pushed_at":"2026-07-27T18:43:06+00:00","maintenance_label":"Active","stars_delta_30d":463,"url":"https://www.graphcanon.com/tools/patchy631-ai-engineering-hub","markdown_url":"https://www.graphcanon.com/tools/patchy631-ai-engineering-hub.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/patchy631-ai-engineering-hub","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=patchy631-ai-engineering-hub","description":"In-depth tutorials on LLMs, RAGs and real-world AI agent applications.","homepage_url":"https://join.dailydoseofds.com","license":"MIT","open_issues":123,"watchers":454,"ai_summary":"A collection of in-depth tutorials that cover a wide range from beginner to advanced concepts in artificial intelligence, including large language models (LLMs), Retrieval-Augmented Generation (RAG) systems, and practical applications of AI agents.","readme_excerpt":"## 🎯 Getting Started\n\nNew to AI Engineering? Start here:\n\n1. **Complete Beginners**: Check out the [AI Engineering Roadmap](./ai-engineering-roadmap) for a comprehensive learning path\n2. **Learn the Basics**: Start with [Beginner Projects](#-beginner-projects) like OCR apps and simple RAG implementations\n3. **Build Your Skills**: Move to [Intermediate Projects](#-intermediate-projects) with agents and complex workflows\n4. **Master Advanced Concepts**: Tackle [Advanced Projects](#-advanced-projects) including fine-tuning and production systems\n\n---\n\n---\n\n## 📜 License\n\nThis repository is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n---","github_created_at":"2024-10-21T10:43:24+00:00","created_at":"2026-07-07T17:36:15.594703+00:00","updated_at":"2026-08-18T00:02:24.372173+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"agents","name":"agents"},{"slug":"ai","name":"ai"},{"slug":"llms","name":"llms"},{"slug":"machine-learning","name":"machine-learning"},{"slug":"mcp","name":"mcp"},{"slug":"rag","name":"rag"}],"trust":{"provenance":{"is_fork":false,"github_id":876064934,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-18T00:02:23.478Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":0,"days_since_push":21,"last_release_at":null,"stars_delta_30d":463,"open_issues_delta_30d":4},"security_summary":{"status":"no_manifest","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:07:04.616Z","medium_count":0,"scan_profile":"mcp_manifest","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-18T00:02:23.919Z"},"languages":{"value":["jupyter notebook"],"source":"github.language","observed_at":"2026-08-18T00:02:23.919Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-18T00:02:23.919Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["The tutorials and projects use Jupyter Notebooks which require Python and a compatible local environment or cloud-based Jupyter services."]},"constraints":null,"when_to_use":["When you are looking for comprehensive learning paths ranging from complete beginners to advanced experts.","If you aim to understand real-world applications and practical implementations of AI agents, along with large language models and RAGs through hands-on projects.","In a situation where you need structured tutorials that progress from simple OCR apps to more complex workflows involving fine-tuning and production-ready systems."],"when_not_to_use":["If your team already has significant proficiency in AI engineering and advanced LLM frameworks, as the content starts from zero knowledge up.","When you specifically need industry-standard proprietary tools or heavily specialized niche applications that go beyond foundational learning covered by this hub.","In scenarios where immediate advanced project results are required; ai-engineering-hub focuses on education through step-by-step tutorials rather than providing ready-made solutions with minimal setup"],"source":"enrich:decision_facts","observed_at":"2026-07-11T12:48:36.977Z"},"constraint_facets":null,"decision_summary":[{"label":"Requirements","value":"The tutorials and projects use Jupyter Notebooks which require Python and a compatible local environment or cloud-based Jupyter services."},{"label":"Adopt for","value":"A collection of in-depth tutorials aiming to cover a wide range from beginner to advanced concepts in AI, including large language models (LLMs), Retrieval-Augmented Generation (RAG) systems and practical applications of"},{"label":"License detail","value":"MIT License"}]}}