🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
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🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
- deep-learning
- deep-learning-tutorial
- pytorch
- gan
🧠 Train a 64M-parameter LLM from scratch in just 2h!
How to create an OS from scratch
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
📗🌐 🚢 Comprehensive and exhaustive JavaScript & Node.js testing best practices (August 2025)
Community guide to securing and improving privacy on macOS.
Best Practices on Recommendation Systems
- machine-learning
- recommender
- ranking
- deep-learning
TranslatedProgrammer Yupi's (程序员鱼皮) complete AI resource collection + zero-basics Vibe Coding tutorial. Shares step-by-step OpenClaw tutorials, ways to use large models (DeepSeek / GPT / Gemini / Claude / GLM), the latest AI news, a complete collection of Prompts, an AI knowledge encyclopedia (Agent Skills / RAG / MCP / A2A), AI programming tutorials (Harness Engineering), guides to using AI tools (Cursor / Claude Code / TRAE / Codex / Copilot), AI development framework tutorials (Spring AI / LangChain), and a guide to monetizing AI products, helping you quickly master AI technology and stay at the forefront of the times. This project is the open-source documentation aiguide, which has been upgraded to the Yupi AI Navigation website (鱼皮 AI 导航网站)
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
🛠️⚡ Step-by-step tutorial to build a modern JavaScript stack.
Gitbook
- micropoor
- micro8
- penetration
Writing an OS in Rust
- kernel
- rust
- operating-system
- x86-64
Translated7 days golang programs from scratch (web framework Gee, distributed cache GeeCache, object relational mapping ORM framework GeeORM, rpc framework GeeRPC etc) A series on writing/implementing things from scratch in 7 days with Go
- learning
- starter-project
- golang
- scratch
llama3 implementation one matrix multiplication at a time
:books: Learn to write an embedded OS in Rust :crab:
- rust
- bare-metal
- raspberry-pi-3
- rpi3
Learning operating system development using Linux kernel and Raspberry Pi
Community guide to using YubiKey for GnuPG and SSH - protect secrets with hardware crypto.
- yubikey
- gpg
- gnupg
- ssh
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
- pytorch
- pytorch-tutorials
- pytorch-tutorials-cn
- deep-learning
Writing a sqlite clone from scratch in C
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
Quantitative analysis, strategies and backtests
- quantitative-finance
- quantitative-trading
- portfolio-management
- risk-management
Demonstrates how to build a live broadcast app(Swift 3)