Mention dask in readme. [skip ci] (#4942)
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XGBoost is an optimized distributed gradient boosting library designed to be highly ***efficient***, ***flexible*** and ***portable***.
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XGBoost is an optimized distributed gradient boosting library designed to be highly ***efficient***, ***flexible*** and ***portable***.
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It implements machine learning algorithms under the [Gradient Boosting](https://en.wikipedia.org/wiki/Gradient_boosting) framework.
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It implements machine learning algorithms under the [Gradient Boosting](https://en.wikipedia.org/wiki/Gradient_boosting) framework.
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XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way.
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XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way.
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The same code runs on major distributed environment (Kubernetes, Hadoop, SGE, MPI) and can solve problems beyond billions of examples.
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The same code runs on major distributed environment (Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of examples.
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License
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License
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Become a sponsor and get a logo here. See details at [Sponsoring the XGBoost Project](https://xgboost.ai/sponsors). The funds are used to defray the cost of continuous integration and testing infrastructure (https://xgboost-ci.net).
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Become a sponsor and get a logo here. See details at [Sponsoring the XGBoost Project](https://xgboost.ai/sponsors). The funds are used to defray the cost of continuous integration and testing infrastructure (https://xgboost-ci.net).
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## Open Source Collective sponsors
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## Open Source Collective sponsors
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[](#backers) [](#sponsors)
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[](#backers) [](#sponsors)
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### Sponsors
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### Sponsors
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[[Become a sponsor](https://opencollective.com/xgboost#sponsor)]
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[[Become a sponsor](https://opencollective.com/xgboost#sponsor)]
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