Explainable ML has been one of the hottest topics in the ML community over the years. There are countless articles on methods and techniques that could be used to enable explainability. How are these techniques actually used in deployed systems? What are the gaps between existing techniques and the needs of production systems? Join us for two fantastic talks that bring forward extensive research conducted by Partnership on AI and University of Cambridge on Explainable ML's reality & roadmap.

Please note: This event will occur in the ET timezone!

Join on Zoom: https://zoom.us/j/99067386368

Agenda

2:00 pm: Welcome & Housekeeping

2:15 pm: "Challenges in Deploying Explainable Machine Learning" (Umang Bhatt, Research @ Partnership on AI)

3:20 pm: "Beyond Feature Importance: Explaining Uncertainty Estimates" (Javier Antorán, PhD @ University of Cambridge)

4:00 pm: Networking in small-group breakout sessions

Hosted By: Rsqrd AI

Note: This event will take place over zoom. Details will be sent on the week of the event.

Rsqrd AI: Explainable ML - Reality & Roadmap