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This lecture by Judea Pearl from UCLA explores the science of cause and effect, examining both theoretical foundations and personalized applications. During this 1 hour and 23 minute presentation at the Institut des Hautes Etudes Scientifiques (IHES), discover how causal reasoning frameworks can be applied across scientific disciplines. Learn about Pearl's influential work in causal inference, which has revolutionized how researchers approach causality in data analysis. Explore the mathematical foundations of causality and understand how these concepts can be implemented in personalized decision-making contexts. The presentation offers valuable insights for researchers, data scientists, and anyone interested in the formal study of causation.
