613: Causal Machine Learning

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 (https://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