AI 튜토리얼

Master the Ollama Python SDK for local LLM development. Learn to generate text, handle multi-turn chats, use vision models, and build AI apps securely.

Build a working demo app that calls all three Microsoft MAI models via Azure speech-to-text, text-to-speech, and image generation, and learn what these models can do.

Discover how to install and run LLMs locally using LM Studio. Keep your data private, chat with documents using built-in RAG, and set up a local API.

Learn how to set up Claude Code inside Cursor, understand the difference between Claude Code and Claude models in Cursor, and decide when each workflow makes sense for your project.

Learn how to run PrismML's fast and efficient 1-bit Bonsai model locally on Windows, from download and setup to WebUI testing, reaching 88.6 tokens per second.

Learn how to install and use the Claude Code VS Code extension, what it can do across your codebase, and how it compares to working from the terminal.

A deep dive into ResNet architecture, covering how residual learning and skip connections solve the vanishing gradient and degradation problems that make training deep neural networks difficult.

Learn how to run GLM 5.1 locally on an H100 GPU with llama.cpp, test it, use the WebUI, and integrate Claude Code.

Learn how to install Google's new AI-optimized CLI, authenticate it, and wire it up to a Gemini-powered RAG pipeline that answers questions about your own Drive files.

Learn how to install and set up Hermes Agent, the open-source AI agent by Nous Research that remembers, learns, and grows smarter with every task.

This step-by-step guide teaches you to build a secure local AI agent with NanoClaw on Windows, connect it to WhatsApp, and control everything from the chat.

Learn how to fine-tune Gemma 4 E4B-it on a human emotions dataset using LoRA, 4-bit quantization, and a single 3090 GPU.