《动手学大模型Dive into LLMs》系列编程实践教程
21 Lessons, Get Started Building with Generative AI
18 Lessons to Get Started Building AI Agents
Covers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning | 涵盖预训练数据、分词器、Transformer、MoE、分布式训练、缩放定律、推理与对齐,6 项渐进代码作业,掌握 LLM 全栈知识
12 Weeks, 24 Lessons, AI for All!
[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)
Examples and guides for using the OpenAI API
📚 从零开始构建大模型
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Google Research
One has no future if one couldn't teach themself.
Learn how to develop, deploy and iterate on production-grade ML applications.
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
Developer Asset Hub for NVIDIA Nemotron — A one-stop resource for training recipes, usage cookbooks, datasets, and full end-to-end reference examples to build with Nemotron models
Learn ML engineering for free in 4 months! Register here 👇🏼
A Comprehensive Guide for Generative AI, Agentic AI, Multimodal AI, Physical AI Interviews. Proven Formula for multiple FAANG offers and more
Examples, end-2-end tutorials and apps built using Liquid AI Foundational Models (LFM) and the LEAP SDK
Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform
WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.
Jupyter notebooks and a video playlist that teach retrieval augmented generation (RAG) step by step, from indexing to generation.
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
A collection of guides and code examples for building AI applications with open models on Nebius Token Factory.