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hanhongyong's Projects

adapt icon adapt

Awesome Domain Adaptation Python Toolbox

adatime icon adatime

Official implementation of AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data

aiplatform_on_k8s icon aiplatform_on_k8s

基于K8S实现一套完整的分布式机器学习训练平台,支持资源调度模块,分布式作业,Jupyter工作环境。面向算法工程师提供方便快捷的算法训练流程管理平台。

awesome-english-ebooks icon awesome-english-ebooks

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

awesome_lists icon awesome_lists

Awesome Lists for Tenure-Track Assistant Professors and PhD students. (助理教授/博士生生存指南)

chatreviewer icon chatreviewer

ChatReviewer: 使用ChatGPT分析论文优缺点,提出改进建议

clearml icon clearml

ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

cloudflarespeedtest icon cloudflarespeedtest

🌩「自选优选 IP」测试 Cloudflare CDN 延迟和速度,获取最快 IP (IPv4 / IPv6)!另外也支持其他 CDN / 网站 IP ~

cloudreve icon cloudreve

🌩支持多家云存储的云盘系统 (Self-deployed file management and sharing system, supports multiple storage providers)

computer-vision-in-action icon computer-vision-in-action

《计算机视觉实战演练:算法与应用》中文电子书、源码、读者交流社区(持续更新中 ...) 📘 在线电子书 https://charmve.github.io/computer-vision-in-action/ 👇项目主页

da icon da

Unsupervised Domain Adaptation Papers and Code

deep-reinforcement-learning-algorithms icon deep-reinforcement-learning-algorithms

32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.

deeplearning-500-questions icon deeplearning-500-questions

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[email protected] 版权所有,违权必究 Tan 2018.06

deeprl icon deeprl

Deep Reinforcement Learning Lab, a platform designed to make DRL technology and fun for everyone

docker-osx icon docker-osx

Run Mac in a Docker! Run near native OSX-KVM in Docker! X11 Forwarding! CI/CD for OS X!

docker-ubuntu-desktop icon docker-ubuntu-desktop

Docker Image for Ubuntu Desktop which support HW GPU accelerated GUI apps. you can access the Container with ssh or remote desktop, just like Cloud VM.

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