Get Started with RAPIDS

Unlock new insights and make data more productive by leveraging RAPIDS to accelerate your python based data science and analytics pipelines. Learn how to use our libraries, accelerate common data science use cases, and access hands-on labs to develop business-critical applications.

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Explore Resources to Get Started With RAPIDS Libraries

Get started with RAPIDS suite of software libraries

cuDF is a GPU DataFrame library that provides a pandas-like API for loading, filtering, and manipulating data. With pandas accelerator mode, it can accelerate pandas workflows on GPUs with zero code changes.

Coming in summer 2024: Accelerated Polars.

Use Case Tutorials

Learn how to accelerate data science in a few short hours in simple technical walk-throughs that pair step-by-step tutorials with notebooks, sample datasets, and benchmarks in example exercises that demonstrate how RAPIDS helps data scientists save time and better leverage their data in ubiquitous data science and machine learning use cases.

Accelerated Data Analysis

Learn how to use RAPIDS cuDF to accelerate data analytics workflows.

This starter kit covers how to use RAPIDS for:

  • Exploratory Data Analysis
  • Time Series Analysis
  • Visualization
  • DataFrame to ML

Get Started

Data Processing at Scale

Explore how to accelerate Apache Spark 3.0 workloads with the RAPIDS Accelerator for Apache Spark.

This starter kit walks through an example use case in retail:

  • Data Processing, including ETL and manipulation functions

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Time Series Forecasting

Build time series forecasting models with RAPIDS cuDF and cuML, which mimic pandas and sci-kit learn.

This starter kit includes two examples of time series workflows:

  • Time Series Analysis

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Learn How Top-Performing Kaggle Grandmasters Win Data Science Competitions

The Kaggle Grandmasters of NVIDIA place in the top 10% of Kaggle Grandmasters worldwide. Learn their tricks of the trade with our Kaggle Grandmaster series that explain how our teams use accelerated data science to create winning recommender systems and predictive models.

Watch video about mastering multilingual recommender systems

Mastering Multilingual Recommender Systems

The KGMoN leveraged transfer learning, model embedding, and other innovative techniques to construct a two-stage pipeline solution for e-commerce product suggestions. This solution won the 2023 KDD Cup.

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Watch video about mastering recommender systems

Mastering Recommender Systems

KGMoN tackled an e-commerce use case by training high-functioning recommendation systems with a dataset that included millions of anonymized user interactions. These strategies placed top 3 in Kaggle’s Otto competition.

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Read blog about predicting credit defaults using time-series models

Predicting Credit Defaults on a Massive Dataset

Jiwei Liu, KGMON, walks through GPU-acceleration in a default prediction use case (top 10 in Kaggle’s American Express competition) that resulted in significantly faster inference times.

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Enterprise Support

With Enterprise Support, you can accelerate your data science workload with the security of guaranteed response times, priority security notifications, regular updates, and access to NVIDIA AI experts. Get your workload working for you faster with NVIDIA AI Enterprise.

Support Options for RAPIDS
Find the right license to deploy, run, and scale RAPIDS for any application on any platform
Features Open Source
For individuals looking to get access to RAPIDS open-source libraries for development
NVIDIA AI Enterprise
For enterprises looking to purchase RAPIDS for deployment.
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Access to All RAPIDS Libraries, with easy to use APIs × ×
Large-scale graph analytics with 35+ accelerated graph algorithms × ×
Machine learning toolkit with 30+ GPU-accelerated algorithms × ×
Scalable with Dask or Apache Spark × ×
Accessible via docker, PIP, Conda (version dependencies: CUDA®, framework backend) × ×
AI Workflows for Cybersecurity, VRP, and more ×
Workload and infrastructure management features ×
Business-standard support, including: ×

Unlimited technical support cases accepted via the customer portal and phone 24/7


Escalation support during local business hours (9:00 a.m. - 5:00 p.m., Monday-Friday)


Timely resolution provided by NVIDIA experts and engineers


Security fixes and priority notifications


Production branches that ensure API stability


Three years of long-term support

Hands-on NVIDIA LaunchPad labs ×

Experience Enterprise Hardware and Software on NVIDIA Launchpad

Work with NVIDIA experts to try live use cases powered by RAPIDS, in NVIDIA provisioned infrastructure with Launchpad.

Predict Prices with Accelerated Data Processing

Train an XGBoost model and predict taxi ride fares with RAPIDS.

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Data Processing, Tokenization, and Sentiment Analysis

Develop and deploy a sentiment analysis model.

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Accelerating Apache Spark With Zero Code Changes

Run GPU-accelerated Spark SQL queries to run an ETL workflow.

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Synthetic Data Generator for Tabular Data

Explore tabular tokenization and preprocess data to train a GPT model.

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Scale Data Science with Domino Data Lab

Develop and deploy a data science project on Domino Data Lab.

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Deploy a Fraud Detection XGBoost Model

Use cuML tools to visualize a fraud detection dataset.

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Develop an AI-based Cybersecurity Solution

Run cybersecurity use cases to analyze the behavior of every user and detect anomalies.

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Next Item Prediction Using Recommendation Systems

Achieve better accuracy for recommendation models.

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RAPIDS libraries are open source, written in Python, and built on Apache Arrow. The software is being developed in partnership with enterprises globally. Download RAPIDS to dramatically accelerate machine learning and data science.

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