Causal inference (Practical AI #220)
With all the LLM hype, it's worth remembering that enterprise stakeholders want answers to "why" questions. Enter causal inference. Paul Hünermund has been doing research and writing on this topic for some time and joins us to introduce the topic. He also shares some relevant trends and some tips for getting started with methods including double machine learning, experimentation, difference-in-difference, and more.
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Chapters
- 0:00 Welcome to Practical AI
- 0:43 Intro to causality & Paul Hünermund
- 5:35 Why causality?
- 8:11 Determinism vs non-determinism
- 11:01 Gaining confidence
- 14:06 Sponsor: Changelog News
- 15:53 Main ways to use causal inference
- 20:09 Making it practical
- 22:50 First steps to take
- 25:10 Some helpful resources
- 27:35 Daniel's practical example
- 33:01 The effects of causal learning
- 37:11 Closing thoughts
- 41:33 Outro
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This episode is 42 minutes long.
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This episode was published on April 25, 2023.
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