カテゴリー

技術

LLM チュートリアル

大規模言語モデルに関する最新ニュース、手法、リソースを追いかけましょう。実践的な手順解説やスキルアップに役立つユースケースを豊富に掲載しています。

その他の技術：

AIエージェントAzureChatGPTDockerExcelGitMongoDBOpenAIPythonR SpreadsheetsSQL人工知能生成AI

2名以上のトレーニングをお考えですか？DataCamp for Businessをお試しください

Claude Opus 4.8 API Tutorial: Tuning the Effort Parameter

Build a Streamlit app that runs Claude Opus 4.8 with adaptive thinking, auto-scores each response with Haiku 4.5, and charts the cost-quality tradeoff.

Aashi Dutt

2026年6月5日

Artificial Intelligence

SGLang Tutorial: Serving Mistral Medium 3.5 Locally

Set up a multi-GPU Docker environment with tensor parallelism and EAGLE speculative decoding to serve Mistral Medium 3.5 128B through an OpenAI-compatible API.

Abid Ali Awan

2026年6月1日

Artificial Intelligence

Multi-Token Prediction Tutorial: How To Speed Up LLMs

Run Qwen3.6 27B on an RTX 3090 and learn how Multi-Token Prediction (MTP) with llama.cpp can boost local LLM inference by almost 2x without upgrading your GPU.

Abid Ali Awan

2026年5月14日

Artificial Intelligence

GPT-Realtime-2 API Tutorial: Three Tests, Three Verdicts

Learn how OpenAI's gpt-realtime-2, gpt-realtime-translate, and gpt-realtime-whisper differ, then test each one with working Python WebSocket code.

Khalid Abdelaty

2026年5月12日

Artificial Intelligence

How to Run DeepSeek V4 Flash Locally

Learn how to run the full DeepSeek V4 Flash model on a single GPU using a modified llama.cpp build and a compatible GGUF file in this hands-on tutorial.

Abid Ali Awan

2026年5月5日

Artificial Intelligence

DeepSeek V4 API Tutorial: Building a Thinking Mode Arena

Learn how DeepSeek V4's three reasoning modes work, and build a Streamlit comparison app that shows when each mode actually wins on quality, speed, and cost.

Aashi Dutt

2026年4月30日

Artificial Intelligence

Fine-Tuning NVIDIA Nemotron-3-Nano On Psychology Q&A Data

Learn to fine-tune NVIDIA Nemotron-3-Nano-4B on a psychology Q&A dataset using an RTX 3090 GPU using LoRA and TRL after downloading the model from Hugging Face.

Abid Ali Awan

2026年4月29日

Artificial Intelligence

Qwen 3.6 Plus API Tutorial: Building an Invoice Processing Pipeline in Python

Learn how to use Alibaba's Qwen 3.6 Plus, Python, and the OpenAI SDK to build an automated invoice processing pipeline with native vision and tool calling.

Bexruz (Bex) Tuychiev

2026年4月27日

Artificial Intelligence

Fine-Tuning Qwen3.6 On a Medical Q&A Dataset

Learn how to fine-tune Qwen3.6 on an H100 NVL GPU using SFT, from dataset preparation and 4-bit loading to training and evaluation.

Abid Ali Awan

2026年4月21日

Artificial Intelligence

LLM As a Judge: A Complete Guide With Hands-On RAG Example

Learn how to build an automated LLM-as-a-judge system to evaluate your RAG pipelines for faithfulness and relevance at scale and bridge the gap in AI testing.

Josep Ferrer

2026年4月20日

Artificial Intelligence

Claude Opus 4.7 API Tutorial: Building a Chart Digitizer

Learn the capabilities of Anthropic’s best publicly available model, Claude Opus 4.7, and build a data science tool that can turn a chart into raw data.

François Aubry

2026年4月20日

AI Agents

Running MiniMax M2.7 Locally for Agentic Coding

In this guide, we will rent an H200 GPU and install llama.cpp, download MiniMax M2.7 GGUF, run it locally, test it in the WebUI, and connect it to OpenCode.

Abid Ali Awan

2026年4月17日

トピック

技術

LLM チュートリアル

Claude Opus 4.8 API Tutorial: Tuning the Effort Parameter

SGLang Tutorial: Serving Mistral Medium 3.5 Locally

Multi-Token Prediction Tutorial: How To Speed Up LLMs

GPT-Realtime-2 API Tutorial: Three Tests, Three Verdicts

How to Run DeepSeek V4 Flash Locally

DeepSeek V4 API Tutorial: Building a Thinking Mode Arena

Fine-Tuning NVIDIA Nemotron-3-Nano On Psychology Q&A Data

Qwen 3.6 Plus API Tutorial: Building an Invoice Processing Pipeline in Python

Fine-Tuning Qwen3.6 On a Medical Q&A Dataset

LLM As a Judge: A Complete Guide With Hands-On RAG Example

Claude Opus 4.7 API Tutorial: Building a Chart Digitizer

Running MiniMax M2.7 Locally for Agentic Coding

トピック

技術