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Refined Gradient Boosting category with binding libraries by @ankane and @PairOnAir.
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‎readme.md‎

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@@ -48,6 +48,7 @@ the word using the `#RubyML` hash tag!
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* [Clustering](#clustering)
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* [Linear classifiers](#linear-classifiers)
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* [Statistical models](#statistical-models)
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* [Gradient boosting](#gradient-boosting)
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- [Applications of machine learning](#applications-of-machine-learning)
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- [Data structures](#data-structures)
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- [Data visualization](#data-visualization)
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### Gradient boosting
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- [xgboost](https://github.com/PairOnAir/xgboost-ruby) - Ruby bindings for XGBoost
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- [xgb](https://github.com/ankane/xgb) - Ruby bindings for XGBoost
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- [lightgbm](https://github.com/ankane/lightgbm) - Ruby bindings for LightGBM
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- [xgboost](https://github.com/PairOnAir/xgboost-ruby) —
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Ruby bindings for XGBoost.
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<sup>[[dep: XGBoost](#xgboost)]</sup>
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- [xgb](https://github.com/ankane/xgb) &mdash;
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Ruby bindings for XGBoost.
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<sup>[[dep: XGBoost](#xgboost)]</sup>
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- [lightgbm](https://github.com/ankane/lightgbm) &mdash;
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Ruby bindings for LightGBM.
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<sup>[[dep: LightGBM](#lightgbm)]</sup>
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## Applications of machine learning
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## Related Resources
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- <a name="lightgbm"></a>
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[LightGBM](https://github.com/microsoft/LightGBM)
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- <a name="xgboost"></a>
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[XGBoost](https://github.com/dmlc/xgboost)
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- <a name="gls"></a>
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[GSL (GNU Scientific Library)][gls]
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- <a name="opencv"></a>

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