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:alt:User guide for uplift modeling and casual inference.
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:alt:User guide for uplift modeling and causal inference.
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Uplift modeling evaluates the effect of communication with clients and selects the group that is most affected.
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This class of tasks is easy to implement, but it is not widely used in the machine learning courses or in the relevant literature.
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In this guide we will try to reveal all the necessary basics for modeling uplift.
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Uplift modeling estimates the effect of communication action on some customer outcome and gives an opportunity to efficiently target customers which are most likely to respond to a marketing campaign.
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It is relatively easy to implement, but surprisingly poorly covered in the machine learning courses and literature.
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This guide is going to shed some light on the essentials of causal inference estimating and uplift modeling.
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