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Optimising Non-Linear Treatment Effects in Pricing and Promotions - Towards Data Science

Retrieved on: 2024-05-25 07:20:14

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Summary

The article by Ryan O'Sullivan illustrates integrating causal reasoning into machine learning models, focusing on optimizing non-linear treatment effects using methods like S-Learner and equations like Michaelis-Menten. Tags and key concepts like regression analysis, estimation theory, and machine learning are intertwined, showcasing practical applications in pricing and promotions.

Article found on: towardsdatascience.com

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