[docs] add winning solutions (#1241)

* add winning solutions

* fix link

* change to table

README.md

@@ -21,7 +21,7 @@ LightGBM is a gradient boosting framework that uses tree based learning algorith
 
 For more details, please refer to [Features](https://github.com/Microsoft/LightGBM/blob/master/docs/Features.rst).
 
-[Comparison experiments](https://github.com/Microsoft/LightGBM/blob/master/docs/Experiments.rst#comparison-experiment) on public datasets show that LightGBM can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. What's more, the [parallel experiments](https://github.com/Microsoft/LightGBM/blob/master/docs/Experiments.rst#parallel-experiment) show that LightGBM can achieve a linear speed-up by using multiple machines for training in specific settings.
+[Comparison experiments](https://github.com/Microsoft/LightGBM/blob/master/docs/Experiments.rst#comparison-experiment) on public datasets show that LightGBM can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. What's more, the [parallel experiments](https://github.com/Microsoft/LightGBM/blob/master/docs/Experiments.rst#parallel-experiment) show that LightGBM can achieve a linear speed-up by using multiple machines for training in specific settings. Benefit from these advantages, LightGBM is being widely-used in many [winning solutions](https://github.com/Microsoft/LightGBM/blob/master/examples/README.md#machine-learning-challenge-winning-solutions) of machine learning competitions.
 
 News
 ----
@@ -97,6 +97,7 @@ LightGBM has been developed and used by many active community members. Your help
 - Contribute to the [tests](https://github.com/Microsoft/LightGBM/tree/master/tests) to make it more reliable.
 - Contribute to the [documents](https://github.com/Microsoft/LightGBM/tree/master/docs) to make it clearer for everyone.
 - Contribute to the [examples](https://github.com/Microsoft/LightGBM/tree/master/examples) to share your experience with other users.
+- Add your stories and experience to [Awesome LightGBM](https://github.com/Microsoft/LightGBM/blob/master/examples/README.md).
 - Open issue if you met problems during development.
 
 Microsoft Open Source Code of Conduct

examples/README.md

@@ -2,3 +2,20 @@ Examples
 ========
 
 You can learn how to use LightGBM by these examples.
+
+
+Machine Learning Challenge Winning Solutions
+============================================
+
+| Place         | Competition   | Solution  |
+| ------------- |:------------- | --------- |
+| 1st     | [Recruit Restaurant Visitor Forecasting](https://www.kaggle.com/c/recruit-restaurant-visitor-forecasting) | [link](https://www.kaggle.com/pureheart/1st-place-lgb-model-public-0-470-private-0-502/comments) |
+| 1st     | [WSDM CUP 2018 - KKBox's Music Recommendation Challenge](https://www.kaggle.com/c/kkbox-music-recommendation-challenge) | [link](https://www.kaggle.com/c/kkbox-music-recommendation-challenge/discussion/45942) |
+| 1st     | [Porto Seguro’s Safe Driver Prediction](https://www.kaggle.com/c/porto-seguro-safe-driver-prediction) | [link](https://www.kaggle.com/c/kkbox-music-recommendation-challenge/discussion/45942) |
+| 1st     | [Quora Question Pairs](https://www.kaggle.com/c/quora-question-pairs) | [link](https://www.kaggle.com/c/porto-seguro-safe-driver-prediction/discussion/44629) |
+| 1st     | [Two Sigma Connect: Rental Listing Inquiries](https://www.kaggle.com/c/two-sigma-connect-rental-listing-inquiries) | [link](https://www.kaggle.com/c/two-sigma-connect-rental-listing-inquiries/discussion/32163) |
+| 1st     | [CIKM2017 AnalytiCup - Lazada Product Title Quality Challenge](http://cikm2017.org/CIKM_AnalytiCup_task3.html) | [link](https://www.kaggle.com/c/two-sigma-connect-rental-listing-inquiries/discussion/32163) |
+| 2nd     | [Two Sigma Connect: Rental Listing Inquiries](https://www.kaggle.com/c/two-sigma-connect-rental-listing-inquiries) | [link](https://www.kaggle.com/c/two-sigma-connect-rental-listing-inquiries/discussion/32148) |
+| 3rd     | [Two Sigma Connect: Rental Listing Inquiries](https://www.kaggle.com/c/two-sigma-connect-rental-listing-inquiries) | [link](https://www.kaggle.com/c/two-sigma-connect-rental-listing-inquiries/discussion/32123) |
+| 3rd     | [Dogs vs. Cats Redux: Kernels Edition](https://www.kaggle.com/c/dogs-vs-cats-redux-kernels-edition) | [link](http://blog.kaggle.com/2017/04/20/dogs-vs-cats-redux-playground-competition-3rd-place-interview-marco-lugo) |
+| 3rd     | [Bosch Production Line Performance](https://www.kaggle.com/c/bosch-production-line-performance) | [link](http://blog.kaggle.com/2016/12/15/bosch-production-line-performance-competition-winners-interview-3rd-place-team-data-property-avengers-darragh-marios-mathias-stanislav) |