An interactive open-access textbook on Machine Learning Systems engineering from Harvard University, integrating the TinyTorch framework with hands-on edge deployment labs, covering the full spectrum from ML fundamentals to system optimization.
An open-source collection of tutorials and runnable scripts for over 30 advanced Retrieval-Augmented Generation (RAG) techniques, including Graph RAG, Agentic RAG, and various retrieval optimization strategies, implemented primarily with LangChain.
Official code repository for the O'Reilly book "Hands-On Large Language Models". Features 12 core chapters and bonus content covering Tokens, Transformers, RAG, and Fine-tuning. Includes 300+ illustrations and runnable Jupyter Notebooks optimized for Colab and local environments.
A comprehensive AI engineering hub featuring 93+ production-ready projects with in-depth tutorials and implementations for LLMs, RAGs, AI Agents, and MCP, covering beginner to advanced skill levels.
A curated collection of resources for Long Chain-of-Thought (Long-CoT) reasoning in LLMs, featuring papers, implementations, and datasets to track the latest advancements in the field.
A tutorial repository by Neural Maze for building WhatsApp AI Agents, guiding developers through deployment and development.
Project information is incomplete; verified data has been retained for future updates.
A systematic collection of reading notes for LLMs top conference papers, covering motivation and method analysis in core areas like PEFT (LoRA/QLoRA), RAG, and Agents (RoleLLM), providing structured learning paths for algorithm engineers.
A curated list of must-read papers and resources on LLM Agents maintained by ZJUNLP, covering single agent capabilities (memory, planning, tool use), multi-agent collaboration, benchmarks, and mainstream development frameworks.
A curated collection of extracted system prompts from popular chatbots like ChatGPT, Claude, and Gemini, helping researchers understand the behavior boundaries of AI models。
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