cuML is a suite of fast, GPU-accelerated machine learning algorithms designed for data science and analytical tasks. Our API mirrors scikit-learn, providing practitioners with the familiar fit-predict …

cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects.

NVIDIA cuML is an open-source CUDA-X™ Data Science library that accelerates scikit-learn, UMAP, and HDBSCAN on GPUs—supercharging machine learning workflows with no code changes …

Sep 18, 2025 · This article offers a hands-on Python introduction to cuML, a Python library from RAPIDS AI (an open-source suite within NVIDIA) for GPU-accelerated machine learning workflows across …

Oct 9, 2025 · Option to build cuML without multiGPU algorithms. Removes dependency on nccl, libcumlprims and ucxx. RAFT's Python and Cython is located in the RAFT repository.

Find out details on featured RAPIDS projects like cuDF, cuML, cuGraph, and more. Also learn about those using our integrated with RAPIDS in our Ecosystem Software Section

This release brings significant improvements to cuML's performance, stability, and developer experience. The highlight is the new Spectral Embedding algorithm, along with major architectural …

Aug 6, 2025 · cuML is a GPU accelerated machine learning library developed by NVIDIA as part of the RAPIDS AI ecosystem.

cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects.

This section provides practical guidance on how to get started with cuML in your own projects to run classic ML algorithms blazingly fast on NVIDIA GPUs. You can simply read through the examples or …