Modeling is a scientific process that requires experimentation to get right. But experimentation is only as effective as the techniques and tools applied to it. At this Summit, we bring together modelers across a wide variety of industries and modeling problems to discuss their approach to experimentation and how this translated to better modeling results. Discussion will touch on techniques to design experiments to ask the right questions, explore experiments to understand modeling problems, and optimize experiments to get the best results. And cases will include experimentation applied to simulations, graph neural networks, transformers, convolutional neural networks, recurrent neural networks, random forests, gradient-boosted trees, reinforcement learning and everything in between.
Attendees and speakers include data scientists, AI leaders, AI platform engineers, researchers, machine learning engineers and deep learning engineers.