Stars
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Datasets, Transforms and Models specific to Computer Vision
Python package built to ease deep learning on graph, on top of existing DL frameworks.
⭐Github Ranking⭐ Github stars and forks ranking list. Github Top100 stars list of different languages. Automatically update daily. | Github仓库排名，每日自动更新
Graph Neural Network Library for PyTorch
Open3D: A Modern Library for 3D Data Processing
This is the repository for the collection of Graph-based Deep Learning for Communication Networks.
为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, m…
RIS-Codes-Collection: A Complete Collection contains the Codes for RIS(IRS) Researches.
经济学人(含音频)、纽约客、卫报、连线、大西洋月刊等英语杂志免费下载,支持epub、mobi、pdf格式, 每周更新
NumPy aware dynamic Python compiler using LLVM
《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。
PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
This repo includes ChatGPT prompt curation to use ChatGPT better.
Hydra is a framework for elegantly configuring complex applications
An opinionated list of awesome Python frameworks, libraries, software and resources.
This is the notes of the way of machine learning study. You may find something useful in it.
PyTorch implementations of deep reinforcement learning algorithms and environments
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
A resource repository for 3D machine learning
A playbook for systematically maximizing the performance of deep learning models.
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023
PyTorch deep learning projects made easy.
来自一位 Pythonista 的编程经验分享，内容涵盖编码技巧、最佳实践与思维模式等方面。
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
Official implementation of our ICML 2023 paper "LinSATNet: The Positive Linear Satisfiability Neural Networks".