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[doc] Add FLAML as a fast tuning tool for XGBoost (#6770)

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Co-authored-by: Qingyun Wu <qiw@microsoft.com>
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Qingyun Wu 2021-03-19 13:47:39 -04:00 committed by GitHub
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## Tools using XGBoost
- [BayesBoost](https://github.com/mpearmain/BayesBoost) - Bayesian Optimization using xgboost and sklearn API
- [FLAML](https://github.com/microsoft/FLAML) - An open source AutoML library
designed to automatically produce accurate machine learning models with low computational cost. FLAML includes [XGBoost as one of the default learners](https://github.com/microsoft/FLAML/blob/main/flaml/model.py) and can also be used as a fast hyperparameter tuning tool for XGBoost ([code example](https://github.com/microsoft/FLAML/blob/main/notebook/flaml_xgboost.ipynb)).
- [gp_xgboost_gridsearch](https://github.com/vatsan/gp_xgboost_gridsearch) - In-database parallel grid-search for XGBoost on [Greenplum](https://github.com/greenplum-db/gpdb) using PL/Python
- [tpot](https://github.com/rhiever/tpot) - A Python tool that automatically creates and optimizes machine learning pipelines using genetic programming.