Example Projects for Data Science Workflows

These example projects demonstrate how to leverage NVIDIA’s RAPIDS suite and other tools for accelerated data science workflows. The following projects showcase:

• GPU-accelerated data processing and analysis using RAPIDS cuDF.

• Machine learning model development with RAPIDS cuML.

• Integration with popular data science platforms like Kaggle.

• End-to-end data science workflows with optimized performance.

These examples are ideal for data scientists and analysts looking to:

• Accelerate their data processing pipelines.

• Scale machine learning workflows.

• Optimize performance for large datasets.

• Integrate GPU acceleration into existing data science workflows.

Example Project on GitHub	Description	Clone and Open	Support Forum
Competition Kernel	An example project to bring your own compute to any Kaggle competition	Open in AI Workbench	Support forum link
RAPIDS CuDF	An example project to explore the RAPIDS cuDF library	Open in AI Workbench	Support forum link
RAPIDS CuML	An example project to explore the RAPIDS cuML library	Open in AI Workbench	Support forum link

Next Steps

• Example Projects for Retrieval Augmented Generation (RAG)

• Example Projects for Fine-Tuning Models

• Example Projects for Blueprint Workflows

• Example Projects using NIM Deployments