tutorial

Pair Claude Desktop on Anthropic with Claude Code routed through Ollama. Visual walkthrough + copy-paste prompt that cuts your Claude Code bill ~90%.

An 18 notebook course that isolates and measures each component of agentic loop engineering on real, industry standard software datasets.

A practical guide to AI: from running your first local model to building your own agents. 52 files covering LLMs, Ollama, RAG, prompt engineering, machine learning, AI agents, and local AI tools.

From-scratch voice agents in Python: end-to-end speech pipelines, runnable chapters, and a small shared library. Local models, explicit streaming behavior.

Build a Python Reflex App with OpenAI, a Neon Postgres + Vector Database, and Deploy to a Virtual Machine

RE:从0开始的RAG学习生活。包含LangChain、LangGraph、LangSmith、PydanticAI等框架和工具的学习教程。

This comprehensive guide provides a universal process for preparing your own speech datasets and training a custom Text-to-Speech (TTS) model.

🖼️ Classify images and extract data from or describe their contents using machine learning

无需预算，使用你的个人数据克隆自己——赛博飞升！Clone yourself by tuning a LLM using your own data.

面向开发者与初学者的 nano-vLLM 交互式源码教程 - 通过 13 个 HTML 互动实验 + 13 章中文教程理解大模型推理引擎

A complete, hands-on roadmap to becoming an AI Engineer, from Python basics to production RAG, Agents, and Fine-Tuning. 10 modules, 20+ notebooks, 15 real projects. Free, open source, built for the community.

Fine-tune the newly released Llama-3.2 lightweight models.

This repository contains a short introduction on the topic of audio and speech processing -- from basics to applications.

The complete open-source LLM curriculum — prompt engineering, RAG, fine-tuning, agents, and production deployment. Beginner to advanced. Python. Free forever.