Engineering Blog - Learnings from Distributed XGBoost on Amazon SageMaker

XGBoost is a popular Python library for gradient boosted decision trees. The implementation allows practitioners to distribute training across multiple compute instances (or workers), which is especially useful for large training sets. One tool used at Zalando for deploying production machine learning models is the managed service from Amazon called SageMaker. XGBoost is already included in SageMaker as a built-in algorithm, meaning that a prebuilt docker container is available. This container also supports distributed training, making it easy to scale training jobs across many instances.