613: Causal Machine Learning
Show notes
Dr. Emre Kiciman, Senior Principal Researcher at Microsoft Research joins the podcast to share his world-leading knowledge on causal machine learning. This episode is brought to you by Datalore (datalore.online/SDS), the collaborative data science platform, and by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • What is causal machine learning? [5:52] • Causal machine learning vs correlational machine learning [10:10] • Emre’s DoWhy open-source library [16:17] • The four key steps of causal inference [21:24] • How and why Emre’s key steps of causal inference will impact ML [26:36] • Emre's thoughts on the future of causal inference and AGI [34:09] • How Emre leverages social media data to solve social problems [38:36] • What's next for Emre's research [46:02] • The software tools Emre highly recommends [55:16] • What he looks for in the data science researchers he hires [58:45] Additional materials: www.superdatascience.com/613
Guests
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