Today we're accompanied by Robert Osazuwa Ness, Machine Learning Research Engineer at ML Startup Gamalon and Instructor at Northeastern University.
Robert, who we had the pleasure of meeting at the Black in AI Workshop at NeurIPS last month, joins us to discuss Causality, and our upcoming study group based around his new course sequence, "Causal Modeling in Machine Learning." In our conversation, we explore what Causality means in various contexts and how that perspective changes across domains and users, what causal models can do that non-causal models aren't as effective at, and real-world applications of causality. We also look at the various tools and packages for causality, areas where it is effectively being deployed in machine learning, like ML in production, and of course the upcoming study group, for which you can find more details
here.
