2022 year 7 month , Nine chapters cloud pole DataCanvas The company released another Breakthrough open source technology achievements ——YLearn Causal learning open source project ！

YLearn Causal learning open source project , yes The world's first open source algorithm toolkit for dealing with the complete process of causal learning in a one-stop way , Took the lead in solving the problem of causal learning “ Cause and effect Find out 、 Causal quantity identification 、 Causal effect estimation 、 Counterfactual inference and strategy learning ” Five key issues , have "One-stop" work style 、 New and complete 、 A wide range of uses Other characteristics , take “ Decision makers ” The use threshold is reduced to the minimum , Realize government and enterprise automation “ Decision making ” Effective improvement of ability .

To help cause and effect AI The wide spread of Technology , Accelerate cause and effect AI Engineering application of ,YLearn The community sincerely invites developers with similar aspirations to create a serious and lively open source causal community side by side with us . This contributor plan is for developers all over the world , You are welcome to take part in , Jointly promote the rapid development of causal learning ！

YLearn Contributor program

In order to help you understand 、 Suggest 、 Development YLearn Causal learning open source project , We provide 3 There are three types of contribution tasks , And thanks for the small gifts carefully prepared for the contributors who completed the task ！ The task is moderately difficult , You can complete all tasks quickly ~

The task list is as follows , Please go to GitHub see （https://github.com/DataCanvasIO/YLearn/issues/16)：

1、 Document class ：

2、 Code class ：

3、 Information class ( Unlimited number of replies )：

Participate in the way

Step 1： open GitHub Contribution links （https://github.com/DataCanvasIO/YLearn/issues/16), Select what you are interested in from the list issue. For document and code tasks, please jump to the corresponding issue Next reply “I will help this one” To claim the task , Our community staff will take this issue Assigned to you , confirm ; For information tasks , Please reply directly .

Step 2： Write and develop claimed issue, Submit... When done pull request（PR）. Be careful ： Submit PR after , Please return to the corresponding issue page , reply PR link .

Step 3：YLearn Community workers will respond to the submitted PR Review the content review, Discuss and communicate with contributors , After reaching a consensus PR Will be merged merge Go to the main project .

Join the community

Nine chapters cloud pole DataCanvas【YLearn Causal learning open source project communication group 】 Start recruiting ！

【YLearn Causal learning open source project communication group 】 We are committed to building a good communication and learning for the majority of friends who are interested in causal learning 、 A platform for resource interaction . Welcome friends who are interested in causal learning , You can add a little helper wechat ：DataCanvas  The group of .

Contribution reward and distribution

In order to actively participate in YLearn Thanks to the contributing developers , We are for all high quality PR Contributors prepared nine chapters of cloud pole DataCanvas Company group favorite “ Badou ” Of Luckybag package ！

（“ Badou ”Luckybag package ： Canvas bag + Neck pillow + Patch + backrest + Mouse pad ）

Prize distribution process ：

Step 1： please PR Contributors should contact according to the following email template YLearn Community ;

a)  Email address ：[email protected]

b)  Email subject ：GitHub contribution – issue #

c)  Email content ： Task links  + GitHub Proof of account screenshot + Express delivery information

Step 2： After information verification , The gift package will be sent by express .

Other instructions

Award criteria ： The task quality selection rules are determined by YLearn Community decision

The deadline for this event is ：2022 year 8 month 31 Japan

Exchange term ： Please take the initiative to provide relevant information to email after the task is completed [email protected], Overdue will be deemed as automatic waiver .

If you encounter any problems in the development process , You are also welcome to send questions to email [email protected] consulting  （* YLearn The community reserves the right of final interpretation ）

If you want to discuss with us YLearn, Also welcome to click the link to leave your question ：https://github.com/DataCanvasIO/YLearn/discussions/19

YLearn The community welcomes you , Causal learning requires your contribution ！