dmlc/xgboost
dmlc/xgboost is a C++ project with 28.6k stars in the AI Tools space. Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
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Quick answers
How active is development on dmlc/xgboost?
The most recent commit recorded on dmlc/xgboost was 11 days ago, based on the GitHub push timestamp. The repository has 8.9k forks — one of the better signals of community interest.
How many stars does dmlc/xgboost have?
dmlc/xgboost has 28.6k GitHub stars — refresh the page for the live number, or check github.com/dmlc/xgboost. TopGit mirrors GitHub's count but does not claim minute-by-minute accuracy.
Is dmlc/xgboost open source?
Yes — dmlc/xgboost ships under the Apache-2.0 license, which makes its source code freely readable (and, depending on license terms, forkable and reusable). Source: github.com/dmlc/xgboost.
What else is in the AI Tools space?
dmlc/xgboost is tracked by TopGit under the AI Tools category, alongside 6 GitHub-tagged topics. Trending and Topics pages list peer repositories of comparable stars and language.
What is dmlc/xgboost?
dmlc/xgboost (dmlc/xgboost) is a C++ project on GitHub. From the project's own README: Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
What language is dmlc/xgboost written in?
dmlc/xgboost is written primarily in C++. GitHub's language field is based on the largest share of bytes in the default branch.
What license does dmlc/xgboost use?
dmlc/xgboost is released under the Apache-2.0 license. Always verify the LICENSE file directly on GitHub for the authoritative terms — license strings can be edited out of sync with a project's actual stance.
Where do I read more about dmlc/xgboost?
This TopGit page is a snapshot — the READ ME tab shows the project's own README content (links stripped, images preserved). The GitHub repository at github.com/dmlc/xgboost is the definitive source.
Read full README in the tab above.