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This repo provides docs and example applications that demonstrate the RAPIDS.ai GPU-accelerated XGBoost-Spark project.

• Mortgage: Scala, Python
• Taxi: Scala, Python
• Agaricus: Scala, Python

Try one of the Getting Started guides below. Please note that they target the Mortgage dataset as written, but with a few changes to EXAMPLE_CLASS, trainDataPath, and evalDataPath, they can be easily adapted to the Taxi or Agaricus datasets.

You can get a small size datasets for each example in the datasets folder. These datasets are only provided for convenience. In order to test for performance, please prepare a larger dataset by following Preparing Datasets. We also provide a larger dataset: Morgage Dataset (1 GB uncompressed), which is used in the guides below.

• Building applications
  • Scala
  • Python
• Getting started on on-prem clusters
  • Standalone cluster for Scala
  • Standalone cluster for Python
  • YARN for Scala
  • YARN for Python
  • Kubernetes
• Getting started on cloud service providers
  • Amazon AWS
    • EMR
    • SageMaker
  • Databricks
  • Google Cloud Platform
• Getting started for Jupyter Notebook applications
  • Apache Toree Notebook for Scala
  • Jupyter Notebook for Python

These examples use default parameters for demo purposes. For a full list please see Supported XGBoost Parameters for Scala or Python

• Scala API
• Python API

• Multi-GPU configuration
• Performance tuning

Please see the RAPIDS website for contact information.

This content is licensed under the Apache License 2.0