Your customers are about to leave? The secrets of recommendation systems revealed.

This article explains how generative AI can be used to improve customer retention by leveraging data and personalizing recommendations. It explores the principles of collaborative filtering, a recommendation technique based on the preferences of similar users, and examines the challenges associated with data sparsity and potential biases.

The episode also explains how "prompt engineering" can be used to optimize AI results by providing precise instructions on how to use the data. Finally, it emphasizes the importance of understanding the concepts of similarity, distance, and regularization to generate relevant and ethical recommendations.

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