cuDF - GPU DataFrame Library

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.

🚚 Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark

Lightweight and extensible compatibility layer between dataframe libraries!

GPU accelerated cross filtering with cuDF.

🚕 A spreadsheet-like data preparation web app that works over Optimus (Pandas, Dask, cuDF, Dask-cuDF, Spark and Vaex)

머신러닝/딥러닝(PyTorch, TensorFlow) 전용 도커입니다. 한글 폰트, 한글 자연어처리 패키지(konlpy), 형태소 분석기, Timezone 등의 설정 등을 추가 하였습니다.

Rapid large-scale fractional differencing with NVIDIA RAPIDS and GPU to minimize memory loss while making a time series stationary. 6x-400x speed up over CPU implementation.

Awesome list of alternative dataframe libraries in Python.

For when your data won't fit in your dataframe

Rapidsai_Machine_learnring_on_GPU

Unlimited Data-Science Benchmarks for Numeric, Tabular and Graph Workloads

Python library to process and classify remote sensing imagery by means of GPUs and ML.

Building NVIDIA's RAPIDS (cuDF, cuML...) in Arch Linux

A simple demo of cuDF which is a RAPIDS GPU-Accelerated Dataframe Library!

The Incredible RAPIDS: a curated list of tutorials, papers, projects, communities and more relating to RAPIDS.

Python from an HPC viewpoint, the most practical tools, and various indispensable libraries for HPC use cases.

GPU-based ML to classify Higgs boson signal from background in particle physics using RAPIDS framework

A compilation of various ML and DL models and ways to optimize the their inferences.