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Introduction to cuML

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Description

cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. This tutorial provides a quick intro to the scikit-learn-like library.

Publisher

NVIDIA

Use Case

Other

Framework

Other

Latest Version

1

Modified

March 31, 2022

Compressed Size

22.36 KB

cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn.

This tutorial will highlight the most commonly used functionality in cuML like splitting and preprocessing data, training and evaluating a model, and building a machine learning pipeline.