Recommenders In the wild - Practical Evaluation Methods

The gap between training a recommender model and actually having a recommender system in production is a topic often neglected. A recommender system is far more than a model which produces good metrics in an offline evaluation. Specifically, the evaluation of various recommendation engines in production is often very different from offline evaluations on a laptop. This tutorial will go through many practical steps and focus on the development, evaluation and, in particular, metrics and A/B tests.