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Conquering DAGs: A Beginner's Guide to Causality
This chapter demystifies Directed Acyclic Graphs (DAGs) for beginners and highlights their role in clarifying assumptions in scientific inquiry. The speakers share their experiences in addressing decision-making challenges in industries like automotive, emphasizing the importance of expert insights and varied data sources. Through discussions on long tail distributions and the notion of identifiability, they explore the complexities of modeling causality and the essential resilience required for success in these fields.