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Recommender systems and high-frequency trading

Practical AI

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From Theory to Practice: The Role of A/B Testing

This chapter explores the challenges of applying theoretical models to real-world scenarios, particularly in trading and recommender systems. It emphasizes the critical role of A/B testing in evaluating system performance and optimizing algorithms by comparing user engagement metrics in live settings.

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