rapidsai-community / notebooks-contribView external linksLinks
RAPIDS Community Notebooks
☆554Feb 3, 2026Updated last week
Alternatives and similar repositories for notebooks-contrib
Users that are interested in notebooks-contrib are comparing it to the libraries listed below
Sorting:
- RAPIDS Sample Notebooks☆578Aug 4, 2023Updated 2 years ago
- GPU accelerated cross filtering with cuDF.☆306Updated this week
- cuML - RAPIDS Machine Learning Library☆5,117Updated this week
- Utilities for Dask and CUDA interactions☆319Feb 7, 2026Updated last week
- cuDF - GPU DataFrame Library☆9,486Updated this week
- ☆22Aug 28, 2020Updated 5 years ago
- cuGraph - RAPIDS Graph Analytics Library☆2,124Updated this week
- A JupyterLab extension for displaying dashboards of GPU usage.☆666Feb 5, 2026Updated last week
- A collection of Machine Learning examples to get started with deploying RAPIDS in the Cloud☆142Nov 1, 2024Updated last year
- RAPIDS GPU-BDB☆108Mar 5, 2024Updated last year
- [ARCHIVED] Dask support for distributed GDF object --> Moved to cudf☆137Jun 27, 2019Updated 6 years ago
- Dockerfile templates for creating RAPIDS Docker Images☆84Updated this week
- ☆98Jun 28, 2023Updated 2 years ago
- CUDA-accelerated GIS and spatiotemporal algorithms☆698Jul 28, 2025Updated 6 months ago
- cuSignal - RAPIDS Signal Processing Library☆733Sep 21, 2023Updated 2 years ago
- ☆94Nov 13, 2025Updated 3 months ago
- A collection of RAPIDS examples for security analysts, data scientists, and engineers to quickly get started applying RAPIDS and GPU acce…☆173May 19, 2023Updated 2 years ago
- A collection of open-source GPU accelerated Python tools and examples for quantitative analyst tasks and leverages RAPIDS AI project, Num…☆309Nov 1, 2024Updated last year
- Demo notebooks inside a docker for end-to-end examples☆112Feb 22, 2018Updated 7 years ago
- ☆31Aug 14, 2020Updated 5 years ago
- Common build environment used by gpuCI for building RAPIDS☆19Jul 25, 2023Updated 2 years ago
- NVIDIA Data Science stack tools☆398Sep 5, 2023Updated 2 years ago
- [ARCHIVED] GPU String Manipulation --> Moved to cudf☆48Sep 24, 2019Updated 6 years ago
- H2Oai GPU Edition☆467Oct 24, 2024Updated last year
- Scalable Machine Learning with Dask☆944Sep 27, 2025Updated 4 months ago
- Fork of dmlc/xgboost for RAPIDS + XGBoost integration☆29May 19, 2023Updated 2 years ago
- Dask tutorial☆1,857Nov 4, 2025Updated 3 months ago
- Work for Mastering Large Datasets with Python☆20Dec 8, 2022Updated 3 years ago
- A JupyterLab extension for displaying dashboards of GPU usage.☆13Aug 24, 2023Updated 2 years ago
- NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale da…☆1,139Oct 23, 2025Updated 3 months ago
- BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.☆2,005Sep 16, 2022Updated 3 years ago
- ☆350Jul 26, 2021Updated 4 years ago
- Quickly and accurately render even the largest data.☆3,508Feb 6, 2026Updated last week
- Tutorial on Multi-Objective Recommender Systems @ KDD 2021☆19Dec 4, 2022Updated 3 years ago
- Forecasting library in python☆13Sep 6, 2019Updated 6 years ago
- Spark RAPIDS plugin - accelerate Apache Spark with GPUs☆960Updated this week
- Cloud provider cluster managers for Dask. Supports AWS, Google Cloud Azure and more...☆145Oct 14, 2025Updated 4 months ago
- Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per s…☆8,468Feb 5, 2026Updated last week
- [ARCHIVED] Dask support for multi-GPU machine learning algorithms --> Moved to cuml☆16Jul 30, 2019Updated 6 years ago