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Patricio Cerda-Mardini

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AUTHORS

Antonio Ossa-Guerra, Denis Parra, Felipe del Río, Manuel Cartagena, Patricio Cerda-Mardini

ABSTRACT

This tutorial serves as an introduction to deep learning approaches to build visual recommendation systems. Deep learning models can be used as feature extractors, and perform extremely well in visual recommender systems to create representations of visual items. This tutorial covers the foundations of convolutional neural networks and then how to use them to build state-of-the-art personalized recommendation systems. The tutorial is designed as a hands-on experience, focused on providing both theoretical knowledge as well as practical experience on the topics of the course.


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