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Causal inference

Practical AI

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Exploring Exciting Trends in Causal Inference and AI

This chapter explores how causal inference informs practical applications in AI and data science, focusing on experimental design and causal discovery. It highlights the importance of heterogeneous treatment effects and the role of benchmarking, ultimately positioning causal inference as an essential element in enhancing current AI methodologies.

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