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https://github.com/ashishpatel26/rapidsai_machine_learning_on_gpu

Rapidsai_Machine_learnring_on_GPU
https://github.com/ashishpatel26/rapidsai_machine_learning_on_gpu

cudf cuml dask dask-ml deep-learning machine-learning machine-learning-algorithms nvidia pandas scikit-learn sklearn

Last synced: 8 months ago
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Rapidsai_Machine_learnring_on_GPU

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README

          

# Rapids.ai Machine learning on GPU [![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://lbesson.mit-license.org/)[![Open Source Love svg1](https://badges.frapsoft.com/os/v1/open-source.svg?v=103)](https://github.com/ellerbrock/open-source-badges/)
[![Awesome Rapidsai](https://img.shields.io/badge/badges-awesome-green.svg)](https://github.com/Naereen/badges)

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![](https://github.com/ashishpatel26/Rapidsai_Machine_learning_on_GPU/blob/main/images/rapidsailogo.jpg?raw=true)

🤩**About Rapids**🤩

- The RAPIDS suite of open source software libraries aim to enable execution of end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposing that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.

![](https://github.com/rapidsai/cudf/raw/branch-21.08/img/rapids_arrow.png)

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### Outline

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1. **10 Min to Pandas and Cudf** - [![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ashishpatel26/Rapidsai_Machine_learning_on_GPU/blob/main/10_Min_to_Pandas_and_Cudf_Comparision_on_GPU.ipynb) [**Nbviewer**](https://nbviewer.jupyter.org/github/ashishpatel26/Rapidsai_Machine_learning_on_GPU/blob/main/10_Min_to_Pandas_and_Cudf_Comparision_on_GPU.ipynb)

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Happy Learning

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