Learning

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

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

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

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

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.

To stop developers from reinventing agent basics by providing 52+ runnable notebooks spanning conversational bots to multi-agent systems.

Official Jupyter notebooks demonstrating how to wire Claude into production tasks like RAG, SQL queries, and multimodal pipelines.

Because the official docs list features, but never show you how to chain them into a production workflow.

It catalogs 42 advanced RAG techniques as runnable notebooks so developers can compare chunking, reranking, and graph retrieval strategies without wiring up every pipeline from scratch.

It catalogs legitimate services offering free API access to large language models, complete with rate limits, model lists, and data-privacy caveats.

Because reading about agents is easier than wiring them up correctly.

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.

A community catalog of `.mdc` files that stops Cursor AI from ignoring your stack and generating irrelevant boilerplate.

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

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

Anthropic published a hands-on, notebook-based course that teaches prompt engineering using its cheapest Claude model.

Official Python notebooks and guides for common OpenAI API tasks.

A free, end-to-end ML systems curriculum that treats the repository itself as the course — textbook, build-your-own framework, hardware kits, simulator, and interview prep included.

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

A curated directory of software, plugins, and frameworks that integrate with the DeepSeek API, maintained by DeepSeek itself.