A collection of sample agents built with Agent Development (ADK)

Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

A Curated Collection of LLM resources (work in progress).

Context engineering is the new vibe coding - it's the way to actually make AI coding assistants work. Claude Code is the best for this so that's what this repo is centered around, but you can apply…

What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Official code repo for the O'Reilly Book - "Hands-On Large Language Models"

Train transformer language models with reinforcement learning.

Jupyter notebooks for the Natural Language Processing with Transformers book

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

Playfully annotated Andrej Karpathy's Neural Networks: Zero to Hero

Understanding Deep Learning - Simon J.D. Prince

Recipe for a General, Powerful, Scalable Graph Transformer

Playfully annotated Andrej Karpathy's minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

An annotated^2 implementation of the Transformer paper.

🧠 A study guide to learn about Transformers

The fastai book, published as Jupyter Notebooks

[NeurIPS'22] Tokenized Graph Transformer (TokenGT), in PyTorch

A collection of resources to study Transformers in depth.