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Distributed Gradient Boosting Machine for Big Data

Gradient Boosting Machine is one of the most powerful algorithms in Machine Learning! Our customers and community has spoken & H2O has implemented it to be at once multi-core & high-scale. Learn about this algorithm in layman terms, and Run/Live Demo from familiar setting of R. 

Earl Hathaway, our resident datascientist, will present where it is applicable, and we can review recent KDD & Kaggle winners. 

Cliff Click will present about implementation and design choices of a Distributed GBM, demonstrating the power of the Algorithm on Big Data.

(moving for bigger venue + one more speaker)

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