Explore and Learn About RAPIDS

Leverage containers, demos, and notebooks from the RAPIDS team and community to explore RAPIDS hands on. For more information about RAPIDS visit rapids.ai

Get started now View RAPIDS on GitHub


Use the RAPIDS install assistant to select your preferred install method and environment. Otherwise, use the steps below to launch a pre-configured docker container with examples.

Run the RAPIDS Container

The RAPIDS Docker containers are configured to run RAPIDS and provide example data/notebooks to get started quickly.

Container Host Prerequisites

  • NVIDIA Pascalâ„¢ GPU architecture or better
  • CUDA 9.2 or 10.0 compatible nvidia driver
  • Ubuntu 16.04 or 18.04
  • Docker CE v18+
  • nvidia-docker v2+

Start Container and Notebook Server

$ docker pull rapidsai/rapidsai:cuda9.2-runtime-ubuntu16.04
$ docker run --runtime=nvidia \
        --rm -it \
        -p 8888:8888 \
        -p 8787:8787 \
        -p 8786:8786 \
(rapids) root@container:/rapids/notebooks# bash utils/start-jupyter.sh

NOTE: This will run JupyterLab on port 8888 on your host machine

Use JupyterLab to Explore the Notebooks

Notebooks can be found in two directories within the container:

  • /rapids/notebooks/cuml - cuML demo notebooks
    • These notebooks have data pre-loaded in the container image and will be decompressed by the notebooks
  • /rapids/notebooks/mortgage - cuDF, Dask, XGBoost demo notebook
    • This notebook requires download of Mortgage Data, see notebook E2E.ipynb for more details

Custom Data and Advanced Usage

See the RAPIDS Demo Container page for more information about using custom datasets and other types of containers that are available.


File an issue here for any unexpected problems encountered with any of the information on this site.