This folder contains the Python and Cython code of the algorithms and ML primitives of cuML, that are distributed in the Python cuML package. CUDA_HOME path/to/cuda_toolkit Inferred by location of ...

This PySpark-compatible API leverages the RAPIDS cuML python API to provide GPU-accelerated implementations of many common ML algorithms. These implementations are adapted to use PySpark for ...

NVIDIA has announced a significant improvement for users of its cuML library by reducing the size of CUDA binaries, enabling direct distribution on PyPI. This marks a pivotal step in making cuML more ...

In this tutorial, we implement NVIDIA cuML as a GPU-accelerated machine learning framework and build a practical workflow that demonstrates how RAPIDS can accelerate familiar data science and machine ...

An end-to-end data science ecosystem, open source RAPIDS gives you Python dataframes, graphs, and machine learning on Nvidia GPU hardware Building machine learning models is a repetitive process.