scikit-learn: machine learning in Python

cuDF - GPU DataFrame Library

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Dataframes powered by a multithreaded, vectorized query engine, written in Rust

Graph-indexed Pandas DataFrames for analyzing hierarchical performance data

Test suite for the PyData Array APIs standard

RAPIDS Memory Manager

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing …

KvikIO - High Performance File IO

cuVS - a library for vector search and clustering on the GPU

CUDA-accelerated GIS and spatiotemporal algorithms

cuML - RAPIDS Machine Learning Library

cuGraph - RAPIDS Graph Analytics Library

WholeGraph - large scale Graph Neural Networks

Python bindings for UCX

GPU accelerated cross filtering with cuDF.

Utilities for Dask and CUDA interactions

cuCIM - RAPIDS GPU-accelerated image processing library

Compatibility layer for NumPy to support the Array API

The fundamental package for scientific computing with Python.

NumPy aware dynamic Python compiler using LLVM

Parallel computing with task scheduling

A batched offline inference oriented version of segment-anything

SciPy library main repository

The Torch-MLIR project aims to provide first class support from the PyTorch ecosystem to the MLIR ecosystem.

A conda-smithy repository for pandas.