lithomas1

pandas

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

array-api-compat

Compatibility layer for NumPy to support the Array API

array-api-tests

Test suite for the PyData Array APIs standard

cucim

cuCIM - RAPIDS GPU-accelerated image processing library

cudf

cuDF - GPU DataFrame Library

cugraph

cuGraph - RAPIDS Graph Analytics Library

cuml

cuML - RAPIDS Machine Learning Library

cuspatial

CUDA-accelerated GIS and spatiotemporal algorithms

cuvs

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

cuxfilter

GPU accelerated cross filtering with cuDF.

dask

Parallel computing with task scheduling

dask-cuda

Utilities for Dask and CUDA interactions

devcontainers

hatchet

Graph-indexed Pandas DataFrames for analyzing hierarchical performance data

kvikio

KvikIO - High Performance File IO

LaTeX-OCR

pix2tex: Using a ViT to convert images of equations into LaTeX code.

numba

NumPy aware dynamic Python compiler using LLVM

numpy

The fundamental package for scientific computing with Python.

pipit

Analyze parallel execution traces using pandas dataframes

polars

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

raft

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 high performance applications.

rapids-cmake

rapids-dask-dependency

rmm

RAPIDS Memory Manager

scikit-learn

scikit-learn: machine learning in Python

scipy

SciPy library main repository

segment-anything-fast

A batched offline inference oriented version of segment-anything

ucx-py

Python bindings for UCX

ucxx

wholegraph

WholeGraph - large scale Graph Neural Networks