Nick Pentreath, Principal Engineer at IBM, explains how in recent years deep learning has seen significant success in a wide range of fields, including computer vision, artificial intelligence, speech, NLP and reinforcement learning. However, until recently, deep learning in recommender systems has received relatively little attention. This conference explores recent advances in this area, both in research and practice. I will explain how deep learning can be applied to recommendation parameters, contextual data management architectures, side information, and time-based models, and compare deep learning approaches to other models of state-of-the-art contextual recommendation, and finally I will explore issues of scalability and model serving. challenges.

Learn more here: https://databricks.com/session/deep-learning-for-recommemender-systems

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