Causal inference (Practical AI #220)
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The Implications of Causality in AI Models
Determinism versus non determinism. Can you kind of distinguish a little bit between the two terms in the sense of if someone is just kind of getting into this the early end data science and they're trying to go wait a minute I thought AI was non deterministic but yet causality is explainable. How do those fit together? There's an interesting sort of intellectual history because the frameworks that we're having in causal inference directed a secret graphs developed by Judea Pearl. They built on actually earlier working AI like Bayesian nets for example.
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