Uplift Modeling

By Alejandro Correa and Maria Fernanda Cortes  This post is part of a series in which I’m discussing several parts of my AI_at_Rappi presentation. In a previous post I discussed a particular algorithm for recommending restaurants called rest2vec, In a follow-up, I discussed how to include financial costs when analyzing a churn model.  This time... Continue Reading →

Maximizing a churn campaign’s profitability with cost-sensitive Machine Learning, part 3

This post is part of a series in which I'm discussing several parts of my AI_at_Rappi presentation. In the last two posts, we first discussed how to evaluate a churn marketing campaign using a financial evaluation measure and then how to estimate the customer lifetime value and also how it is possible to design experiments... Continue Reading →

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