KO
|
EN
gitlite — search
Search
#typescript
#ai-agents
#deepseek-harness
#dsh-plugin
#open-source
#ai
#claude-code
#cli
#windows
#codex
#developer-tools
#dsh
causality4ml
★ 80
Open GitHub ↗
把因果思维融入机器学习中
Download README (.md)
Explore Similar Repositories
ImagePickerView
:
ImagePickerView wraps UIImagePickerController for SwiftUI.
govbase
:
Govbase is an open, crowdsourced database of projects and tools in online governance. Data hosted at https://airtable.com/shrgnUrj0dqzZDsOd
Chatbot
:
Hybrid Conversational Bot based on both neural retrieval and neural generative mechanism with TTS.
1y
:
A template project to build a short URL manager with Eleventy
ecs-microservices-orchestration
:
:cloud: :whale: :zap: :rocket: :package: Complete microservices orchestration on ECS on AWS using Terraform
// repository documentation
Was this content helpful?
★ 0
(0 ratings)
Select Rating:
★
★
★
★
★
Submit Feedback
Recent Feedback
×
Download README
Do you want to download the
README.md
file for
causality4ml
?
Download (.md)
# Causality for Machine Learning pdf: https://arxiv.org/abs/1911.10500 把因果思维融入机器学习中, 教会机器因果思维，构建具备因果思维的AI系统是 Judea Pearl 近三十的学术主要追求。本项目的主要目的是围绕嚼碎 Bernhard Scholkopf 的最新论文 Causality for Machine Learning 这个核心任务，提供一个 starters for causality research 抱团取暖的机会，构建一个因果研究的开放互助社区。 更具体的的来说，首先我们嚼碎论文 Causality for Machine Learning by the following steps: - 给出论文一个中文翻译 see [overleaf project](https://www.overleaf.com/read/ycvzvfbhtbfj) - 扩展和解释论文理论的内容, see [overleaf project](https://www.overleaf.com/read/ycvzvfbhtbfj) - 扩展论文代码实践方面的内容，给出论文中涉及结论的 EndToEnd examples with [colab project](https://drive.google.com/open?id=1nnd_03vP2US1Hm4hllCkHgI7omqz51W5). - 展示相关内容 on [google blog of causality4ml](https://sites.google.com/view/causality4ml/home) and [arxiv](https://www.overleaf.com/read/ycvzvfbhtbfj) 我们希望围绕这个论文建立一个开放互助社区 for starters in causality， 社区的研究目标是希望能够 teach machine cause and effect, 希望构建通过小图灵测试的AI系统，even hope we can implement free will on AI。We aim to help starters but still some requirements including: - 您能够轻松的科学上网，使用 google site, overleaf, colab, gmail 等服务。 - 您有一定的数学，物理，计算机科学，信息论，概率统计，机器学习和 python 编程的基础知识。 - 您有着原始的好奇心，热爱探索和思考。 如果您满足这些条件，请加入我们的开放互助社区，send me a email (zj3712@gmail.com) with your basic information so we can have a plan，一起把这个论文任务完成，在因果研究这条艰难的道路，我们在你身边。 友情链接： - [Causal Inference Zero to All](https://sites.google.com/view/causal-inference-zerotoall/home) - [Life and Intelligence, Strong AI](https://sites.google.com/view/strong-ai/home)
