Learning

A community knowledge base that reverse-engineers hundreds of GPT-Image2 examples into structured, agent-ready prompt protocols.

MiniMind is an educational training ground that rebuilds every stage of a modern language model—from tokenizer to RLHF—in raw PyTorch so you can see the gears turning instead of just calling high-level APIs.

This curriculum closes the gap between calling AI APIs and understanding the loss curves underneath.

Hello-Agents is a free, 16-chapter curriculum that teaches developers to construct truly AI-driven agents from first principles rather than wiring no-code workflows.

To turn graduate-level NLP and AI safety lectures into runnable Jupyter notebooks that anyone can break, watermark, or align.

This repo open-sources a full Chinese textbook on AI agent engineering—complete with Markdown source, compiled PDF, and runnable Python demos for every chapter.

Why rebuild the same RAG pipeline or agent loop from scratch when you can fork a working template instead?

A crowdsourced archive of leaked and reverse-engineered system prompts that exposes the hidden scaffolding behind major AI models and agents.

A living archive of extracted system prompts from Anthropic, OpenAI, Google, and xAI that exposes the hidden instructions shaping tone, tools, and guardrails.

To teach agentic design patterns through videos, notebooks, and documentation auto-translated into more than 50 languages.

It teaches how LLMs work by implementing tokenization, attention, pretraining, and finetuning in pure PyTorch, one notebook at a time.

A curated registry of reusable instruction packages that keep Claude and other agents from reinventing the wheel on every task.

It exists to teach developers how to build generative AI applications through 21 modular lessons that mix conceptual explainers with working Python and TypeScript code.

It collects official skill definitions from engineering teams so AI agents don't have to improvise.

A structured 12-week curriculum that teaches symbolic AI, neural nets, and even genetic algorithms—without pretending deep math or cloud ML don't exist.

Curated tutorials and tool reviews covering vibe coding, DeepSeek, Cursor, and the rest of the generative-AI menagerie, maintained as a free, open-source knowledge base.

An open-source Chinese textbook that binds math, code, and critical thinking into a single, living resource for deep learning.

This repo exists to sort the scattered open-source AI agent ecosystem into an industry-by-industry directory, saving you from GitHub search purgatory.

To teach developers agent engineering from scratch using smolagents, LangGraph, and LlamaIndex, capped by an automated benchmark.

Open-sources the exact LLM prompts and agent skills that researchers at MSRA, ByteDance Seed, and top Chinese universities use to write and polish papers.