Scaling Python with Dask and Ray: A Hands-On Approach to Distributed Computing
The workshop is designed for researchers seeking to optimize their workflows for large-scale data processing and parallel computing. Participants will explore the fundamentals of distributed computing with Python, learning how to leverage Dask for efficient task parallelism and Ray for scalable machine learning and reinforcement learning applications. Through hands-on exercises, attendees will gain practical experience in deploying these tools to handle massive datasets, optimize computational resources, and streamline workflows.
Presented by Robert Kalescky
- Date:
- Thursday, January 23, 2025
- Time:
- 3:30pm - 5:00pm
- Hosted by:
- O'Donnell Data Science and Research Computing Institute
- Space:
- Fondren Library 110
- Audience:
- Faculty/staff Graduates Undergraduates
- Categories:
- Scholarship and Research > Computational Skills
Any person who requires a reasonable accommodation on the basis of a disability in order to participate in this program should contact Contact Name and email at least one week prior to the event to arrange for the accommodation.