Popular GitHub Repositories for Graph Processing

? Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

ComfyUI docker images for use in GPU cloud and local environments. Includes AI-Dock base for authentication and improved user experience.

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

Learn how to design, develop, deploy and iterate on production-grade ML applications.

中文分词 词性标注 命名实体识别 依存句法分析 成分句法分析 语义依存分析 语义角色标注 指代消解 风格转换 语义相似度 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁转换 自然语言处理

? Industrial-strength Natural Language Processing (NLP) in Python

Cross-platform, customizable ML solutions for live and streaming media.

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.

? Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

Deezer source separation library including pretrained models.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration.

deep learning for image processing including classification and object-detection etc.

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

Graph Neural Network Library for PyTorch

CVPR 2025 论文和开源项目合集

? Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

? The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。