Co-authors: Sneha Chaudhari, Mahesh Joshi, and Gungor Polatkan In part 1 of this series, we shared a high-level overview of our course recommendation engine for LinkedIn Learning. First, we provided details on the offline and online components of the system design. Later on, we discussed the three main components of the recommendation engine that are key for...
Recommender Systems Articles
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Co-authors: Sneha Chaudhari, Mahesh Joshi, and Gungor Polatkan LinkedIn Learning is a platform where LinkedIn members have the opportunity to develop the relevant skills needed to achieve their professional goals. The Learning AI team continually advances the large-scale content recommendation engine for LinkedIn Learning, serving over 690M LinkedIn members and...
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On Aug. 15, 2016, the Machine Learning Algorithm team at LinkedIn gave a hands-on tutorial on how to build recommender systems using our recently open-sourced machine learning library Photon ML at the KDD conference. We were excited to see a large crowd that could not fit into the room gathered to learn this topic and the strong interest in the data mining...
- Topics:
- machine learning,
- Photon ML,
- Recommender Systems
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LinkedIn makes extensive use of item-based collaborative filtering, which showcases relationships between pairs of items based on the...
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Search plays an important role in online social networks such as LinkedIn, as it provides an essential mechanism for discovering...
- Topics:
- Recommender Systems,
- Paper,
- Search,
- Analytics