Jupyter Notebook のリポジトリ

AirLLM 2.8T LLM inference with single 4GB GPU

18 Lessons to Get Started Building AI Agents

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.

12 Weeks, 24 Lessons, AI for All!

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Anthropic's Interactive Prompt Engineering Tutorial

Google Research

Examples and guides for using the OpenAI API

Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. Join the course here 👇🏼

This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

10 Weeks, 20 Lessons, Data Science for All!

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

Notebooks using the Hugging Face libraries 🤗

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

《Pytorch实用教程》（第二版）无论是零基础入门，还是CV、NLP、LLM项目应用，或是进阶工程化部署落地，在这里都有。相信在本书的帮助下，读者将能够轻松掌握 PyTorch 的使用，成为一名优秀的深度学习工程师。

21 Lessons, Get Started Building with Generative AI

The fastai deep learning library

A game theoretic approach to explain the output of any machine learning model.

Python programs, usually short, of considerable difficulty, to perfect particular skills.