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Elements of Causal Inference
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for cl...
Freud on Madison Avenue
What do consumers really want? In the mid-twentieth century, many marketing executives sought to answer this question by looking to the theories of Sigmund Freud and his followers. By the 1950s, Freudian psychology had become the adman's most powerful new tool, promising to plumb the depths of shoppers' subconscious minds to access the irrational desires beneath their buying decisions. That the unconscious was the key to consumer behavior was a new idea in the field of advertising, and its impact was felt beyond the commercial realm. Centered on the fascinating lives of the brilliant men and women who brought psychoanalytic theories and practices from Europe to Madison Avenue and, ultimately...
