Prompt Engineering, Generative AI, and LLM Guide by Learn Prompting | Join our discord for the largest Prompt Engineering learning community
- gpt-3
- prompting
- prompt-engineering
- gpt3
Repository Index
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TranslatedA beginner's bible for AI that doesn't play at being obscure or cater to a niche few, easy to grasp for everyone from students to engineers. It covers neural networks to large models, top-level design to micro-level principles, and engineering implementation to algorithm fundamentals. After studying it, you will thoroughly understand why the seemingly unremarkable ability of next-token prediction can change the world, and you will also discover that AI is not as mysterious or as unattainable as imagined. Let's just beat it !
- ai
- engineering
- llm
- neural-network
Examples and tutorials to help developers build AI systems
🛠️ Awesome tools & guides for harness engineering.
Translated"PyTorch Practical Tutorial" (Second Edition): whether you are starting from zero, working on CV, NLP, or LLM project applications, or moving on to advanced engineering deployment, it's all here. We believe that with the help of this book, readers will be able to master the use of PyTorch with ease and become an excellent deep learning engineer.
- computer-vision
- deepsort
- diffusion-models
- onnx
Translated"Large Language Models" (《大语言模型》), authors: Zhao Xin, Li Junyi, Zhou Kun, Tang Tianyi, Wen Jirong
- artificial-intelligence
- deep-learning
- deep-neural-networks
- deep-reinforcement-learning
TranslatedOpenClaw Chinese tutorial (4,500+ Stars · printed book published): installation, configuration, Skills, Feishu integration, and pitfalls to avoid | For the author's new GPT-6 / Codex / Claude Code projects, see the top of the README
- openclaw
- openclaw-skills
- agent-skills
- ai-agent
Curated tutorials and resources for Large Language Models, AI Painting, and more.
A comprehensive list of papers using large language/multi-modal models for Robotics/RL, including papers, codes, and related websites
🚀 Awesome System for Machine Learning ⚡️ AI System Papers and Industry Practice. ⚡️ System for Machine Learning, LLM (Large Language Model), GenAI (Generative AI). 🍻 OSDI, NSDI, SIGCOMM, SoCC, MLSys, etc. 🗃️ Llama3, Mistral, etc. 🧑💻 Video Tutorials.
- large-language-models
- ai-infra
- genai
- mlsys
TranslatedNeeding only a Python foundation, build large language models from scratch; build GLM4\Llama3\RWKV6 step by step from scratch, to gain a deep understanding of how large models work
Translated🇨🇳 Complete collection of OpenClaw use cases in Chinese | 50 real-world scenarios | China-specific cases + adaptations of overseas cases for use in China | Office automation · Content creation · Operations & maintenance · AI assistants · Knowledge management | Beginner-friendly
- ai-agent
- ai-assistant
- ai-automation
- ai-tools
Data Science Roadmap from A to Z
🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴
- aws
- bytewax
- comet-ml
- generative-ai
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
- agentic-ai
- agentic-rag
- agents
- rag
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
- deep-learning
- d2l
- data-science
- pytorch-implmention
Translated《御舆：解码 Agent Harness》(Yuyu, "Imperial Carriage: Decoding the Agent Harness"): 420,000 characters dissecting the Harness skeleton and nervous system of AI Agents — an in-depth analysis of the Claude Code architecture, 15 chapters from the conversation loop to building your own Agent Harness. Online reading website:
TranslatedSharing AI Infra knowledge & code exercises: PyTorch, vLLM/SGLang, introductions to the slime/vime frameworks⚡️, performance acceleration🚀, large model fundamentals🧠, AI software and hardware🔧, and more
Numbers every LLM developer should know
MongoDB's Generative AI Showcase: an exhaustive collection of examples and sample applications covering Retrieval-Augmented Generation (RAG), AI agents, and industry-specific use cases.
AI system design guide for engineers building production AI systems and evals.
- agentic-ai
- agentic-workflow
- artificial-intelligence
- aws
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
- gpu-acceleration
- large-language-models
- llm
- llm-inference
A curated list of resources for using LLMs to develop more competitive grant applications.
- generative-ai
- grant-proposals
- grants
- llms
Everything you need to know to build your own RAG application
- agentic-rag
- chatbot
- llm
- machine-learning