Add resource "Deep Neural Networks for YouTube Recommendations" Accepted
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Add Recommendation Systems
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- Recommendation Systems
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- Welcome to Recommendation Systems! We've designed this course to expand your knowledge of recommendation systems and explain different models used in recommendation, including matrix factorization and deep neural networks.
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- https://developers.google.com/machine-learning/recommendation
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Add Deep Neural Networks for YouTube Recommendations
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- Deep Neural Networks for YouTube Recommendations
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- Paper
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- 2016-09-07
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- YouTube represents one of the largest scale and most sophisticated industrial recommendation systems in existence. In this paper, we describe the system at a high level and focus on the dramatic performance improvements brought by deep learning. The paper is split according to the classic two-stage information retrieval dichotomy: first, we detail a deep candidate generation model and then describe a separate deep ranking model. We also provide practical lessons and insights derived from designing, iterating and maintaining a massive recommendation system with enormous user-facing impact.
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- https://storage.googleapis.com/pub-tools-public-publication-data/pdf/45530.pdf
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- ISBN: 9781450340359
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Add Recommender system
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- Recommender system
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- A recommender system, or a recommendation system (sometimes replacing 'system' with a synonym such as platform or engine), is a subclass of information filtering system that seeks to predict the "rating" or "preference" a user would give to an item. They are primarily used in commercial applications. Recommender systems are utilized in a variety of areas and are most commonly recognized as playlist generators for video and music services, product recommenders for online stores, or content recommenders for social media platforms and open web content recommenders. These systems can operate using a single input, like music, or multiple inputs within and across platforms like news, books, and search queries. There are also popular recommender systems for specific topics like restaurants and online dating. Recommender systems have also been developed to explore research articles and experts, collaborators, and financial services.
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- https://en.wikipedia.org/?curid=596646
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Add YouTube recommender system
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- YouTube recommender system
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- The way YouTube serves / recommends its video content to users.
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Add YouTube
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- YouTube
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- YouTube is an American online video-sharing platform headquartered in San Bruno, California. Three former PayPal employees—Chad Hurley, Steve Chen, and Jawed Karim—created the service in February 2005. Google bought the site in November 2006 for US$1.65 billion; YouTube now operates as one of Google's subsidiaries. YouTube allows users to upload, view, rate, share, add to playlists, report, comment on videos, and subscribe to other users. It offers a wide variety of user-generated and corporate media videos. Available content includes video clips, TV show clips, music videos, short and documentary films, audio recordings, movie trailers, live streams, and other content such as video blogging, short original videos, and educational videos.
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- https://en.wikipedia.org/?curid=3524766
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Add Recommender system relates to Deep Neural Networks for YouTube Recommendations
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Add Recommender system treated in Recommendation Systems
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Add YouTube recommender system treated in Deep Neural Networks for YouTube Recommendations
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Add YouTube recommender system subtopic of YouTube
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