This repository contains examples of how to accelerate common Python data science libraries using NVIDIA GPUs. Each notebook demonstrates a different library and shows how to enable GPU (CUDA) acceleration with minimal code changes.
gpu-computing status-active ai-ml-portfolio status-stable lang-jupyter scope-micro value-educational framework-matplotlib framework-pandas framework-scikit-learn ai-ml-portfolio-ml gpu-scientific gpu-deep-learning gsc-cuda-kernel
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Updated
May 19, 2026 - Jupyter Notebook