Open hcho3 opened 3 years ago
@hcho3 Could you please assign this to me? I would like to work on this & will update you regarding the PR as soon as possible?
@divya661 Thanks for taking interest in this. Assigned. From what I understand, there's no limit on the number of participants, so many people can work on the same topic. Especially for this issue, we can submit different solutions from different sources but still count as contribution.
@hcho3 @trivialfis is this still open ?
@Wittty-Panda Yes, this issue is still open. Feel free to add more.
okay ,sir. I will do my best.
@hcho3 do i have to make another section for data science or just add them in machine learning one ?
@Wittty-Panda Just add them to the section titled Machine Learning Challenge Winning Solutions
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okay sir
@hcho3 can you please check pull request #6222 I have added 2 winners as per your instructions , if you find it useful please merge and add hacktoberfest-accepted tag. Thank you for giving me a chance to contribute. #6222
Hello @hcho3 , I would like to contribute to this issue, please could you assign this to me. I will update the readme and create a pull request
Hi, @rshn1994 thank you for the offer! Feel free to open PRs.
The demo directory shows a list of winning solutions for data science competitions that used XGBoost: https://github.com/dmlc/xgboost/blob/master/demo/README.md#machine-learning-challenge-winning-solutions
The list hasn't been updated since October 2017. It would be great if we can update this list.
How to update the list.
https://www.kaggle.com/competitions is a great place to start. For each completed competition, look for the first, second, and third-place solutions. If they used XGBoost (even as part of ensemble), create a pull request to add them to https://github.com/dmlc/xgboost/blob/master/demo/README.md.
There are other data science competitions as well. For example, XGBoost was used in the first winning solution of ACM RecSys 2020 Challenge.