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Learn how to build and execute end-to-end GPU-accelerated data science workflows that enable you to quickly explore, iterate, and get your work into production. Using the RAPIDS™-accelerated data science libraries, you’ll apply a wide variety of GPU-accelerated machine learning algorithms, including XGBoost, cuGRAPH’s single-source shortest path, and cuML’s KNN, DBSCAN, and logistic regression to perform data analysis at scale. More information.

 

 

Presented by Tue Vu

Date:
Thursday, February 29, 2024
Time:
10:00am - 1:00pm
Hosted by:
O'Donnell Data Science and Research Computing Institute
Space:
Fondren Library, Red 109
Audience:
  Faculty/staff     Graduates     Undergraduates  
Categories:
  Scholarship and Research > Computational Skills  
Registration has closed.

Any person who requires a reasonable accommodation on the basis of a disability in order to participate in this program should contact Tue Vu at least one week prior to the event to arrange for the accommodation. 

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