Starred repositories
An opinionated list of Python frameworks, libraries, tools, and resources
Repo for counting stars and contributing. Press F to pay respect to glorious developers.
All Algorithms implemented in Python
🙃 A delightful community-driven (with 2,400+ contributors) framework for managing your zsh configuration. Includes 300+ optional plugins (rails, git, macOS, hub, docker, homebrew, node, php, python…
A curated list of awesome Go frameworks, libraries and software
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
A modern GUI client based on Tauri, designed to run in Windows, macOS and Linux for tailored proxy experience
程序员在家做饭方法指南。Programmer's guide about how to cook at home (Simplified Chinese only).
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Magnificent app which corrects your previous console command.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Models and examples built with TensorFlow
《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。
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…
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
Apache ECharts is a powerful, interactive charting and data visualization library for browser
The official gpt4free repository | various collection of powerful language models | opus 4.6 gpt 5.3 kimi 2.5 deepseek v3.2 gemini 3
⚡ Delightful Node.js packages and resources [BECAUSE OF TOO MUCH SPAM AND LOW-QUALITY SUBMISSIONS, SUBMISSIONS ARE PAUSED UNTIL SEPTEMBER]
A cross-platform, OpenGL terminal emulator.
Resumes generated using the GitHub informations
Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.
The all-in-one AI productivity accelerator. On device and privacy first with no annoying setup or configuration.
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06