Strategies for Machine Learning Reproducibility

In this webinar, we will present the sources that can lead to unintentional irreproducibility in machine learning research. By attending, you will gain a solid grasp of the common pitfalls that can undermine the reproducibility of your work. This presentation will also provide you with valuable insights and practical ideas to help you achieve reproducibility in machine learning research. Date: August 22, 2023
Speakers include: Odd Erik Gundersen is an adjunct associate professor at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway, where he teaches courses and supervises master students in AI; and Kevin Coakley is a Senior Systems and Cloud Integration Engineer at the San Diego Supercomputer Center, UC San Diego where he supports the cloud infrastructure for multiple projects. Kevin’s research interest is in Computer Science where he focuses on reproducibility in Machine Learning.
Hosted by the FAIR in ML, AI Readiness, & Reproducibility Research Coordination Network www.farr-rcn.org/
This work is supported through the NSF award #2226453.