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Nowadays we are offered an increasing number of options to choose from. While this is seen as a positive thing, it can be overwhelming when choosing the best option for us. In this context, recommender systems have been getting increasing importance. In this rootlabs session we will explore how recommender systems work, hardships and how machine learning and neural networks can be applied in such systems. Supporting documentation: - Semantic Scholar: https://pages.semanticscholar.org/about-us - Google Developers: https://developers.google.com/machine-learning/recommendation/collaborative/basics - Neural Collaborative Filtering: https://arxiv.org/pdf/1708.05031.pdf - Demo (Google Collab): https://colab.research.google.com/github/murilo-cunha/inteligencia-superficial/blob/master/_notebooks/2020-09-11-neural_collaborative_filter.ipynb - Demo (Binder): https://mybinder.org/v2/gh/murilo-cunha/inteligencia-superficial/master?filepath=_notebooks%2F2020-09-11-neural_collaborative_filter.ipynb

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