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 Building Recommender Systems with PyTorch - KDD 2020 Tutorial
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-*Dheevatsa Mudigere, Maxim Naumov, Geeta Chauhan, Joe Spisak*
+*Dheevatsa Mudigere, Maxim Naumov, Narine Kokhlikyan, Amanpreet Singh, Geeta Chauhan, Joe Spisak*
 
 In this tutorial we show how to build deep learning recommendation systems and resolve the associated interpretability, integrity and privacy challenges. We start with an overview of the PyTorch framework, features that it offers and a brief review of the evolution of recommendation models. We delineate their typical components and build a proxy deep learning recommendation model [DLRM](https://github.com/facebookresearch/dlrm) in PyTorch. Then, we discuss how to interpret recommendation system results as well as how to address the corresponding integrity and quality challenges.