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Mar 31 2022

Introduction to RAPIDS: End-to-End Accelerated GPU Data Science

March 31, 2022

3:00 PM - 4:30 PM


Traditional CPU-driven data science workflows can be cumbersome, but with the power of GPUs, your teams can make sense of data quickly to drive business decisions.
The RAPIDS suite of open source software libraries gives you the freedom to execute end-to-end data science pipelines entirely on GPUs through user-friendly Python interfaces. RAPIDS data science libraries will enable you to quickly explore, iterate, and get your work into production.
This tutorial will teach you how to use the RAPIDS software stack from Python, including cuDF (a DataFrame library interoperable with Pandas), and cuML (a machine learning library that provides GPU-accelerated versions of the algorithms in scikit-learn).
In order to be successful in this course, you will need the following: Experience with Python, ideally including Pandas and NumPy.

Learning objectives

  • Implement GPU-accelerated data preparation and feature extraction using cuDF
  • Apply a broad spectrum of GPU-accelerated machine learning tasks using cuML algorithms


Registration for this training is closed.


Ana Marija Sokovic

Date posted

Jan 20, 2022

Date updated

Mar 11, 2022