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The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, and more.
A visual no-code/code-free web crawler/spider易采集：一个可视化浏览器自动化测试/数据采集/爬虫软件，可以无代码图形化的设计和执行爬虫任务。别名：ServiceWrapper面向Web应用的智能化服务封装系统。
Obsidian Template for combining P.A.R.A with Periodic Notes(LifeOS for Obsidian)
Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复
程序员在家做饭方法指南。Programmer's guide about how to cook at home (Simplified Chinese only).
Chanify is a safe and simple notification tools. This repository is command line tools for Chanify.
人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial…
Sequence modeling benchmarks and temporal convolutional networks
一款轻量级、高性能、功能强大的内网穿透代理服务器。支持tcp、udp、socks5、http等几乎所有流量转发，可用来访问内网网站、本地支付接口调试、ssh访问、远程桌面，内网dns解析、内网socks5代理等等……，并带有功能强大的web管理端。a lightweight, high-performance, powerful intranet penetration proxy serv…
Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.
Now we have become very big, Different from the original idea. Collect premium software in various categories.
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
《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。
Code to accompany Mastering Data Science from PT press
QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
100-Days-Of-ML-Code中文版
Data Science Using Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
Real Time Market Trading Platform
Dockerized shadowsocks with Haproxy and Supervisord
Docker compose files for Aria2+ AriaNg+ filerun/ Nextcloud/ h5ai + Plex. 图形化BT，磁力，离线下载，文件管理，播放，投屏
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize, and with many additional classes and methods for curve fitting.