Co-authors: Benjamin Le, Daniel Gmach, Aman Grover, Roshan Lal, Jerry Lin, Austin Lu, Qingyun Wan, and Leighton Zhang Feature engineering is foundational for building artificial intelligence (AI) that powers products at LinkedIn. Recently, “representation learning” or “feature learning” has started replacing manually engineered features, as they provide...
artificial intelligence Articles
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Co-authors: Parag Agrawal, Ankan Saha, Yafei Wang, Aastha Nigam, and Eric Lawrence Figure 1: A heterogeneous social network LinkedIn’s “People You May Know” (PYMK) feature has long been used by our members to form connections with other members and expand their networks. As member networks become more heterogeneous, the People You May Know tab (MyNetwork tab...
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Our logo is inspired by the chameleon: You can enable personalization on your ranking model with GDMix, bringing a personalized experience to every user, like a chameleon that can match its surroundings. Co-authors: Jun Shi, Chengming Jiang, Aman Gupta, Mingzhou Zhou, Alice Wu, Yunbo Ouyang, Jun Jia, Huiji Gao, and Bo Long Millions of members come to LinkedIn...
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Co-authors: Chiachi Lo, Bohong Zhao, and Elina Lin When we launched a major redesign of LinkedIn’s mobile application and desktop web...
- Topics:
- relevance,
- artificial intelligence,
- Feed Personalization ,
- Data
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The internet software industry has moved away from long development cycles and dedicated quality assurance (QA) stages, toward a...
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Co-authors: Sriram Vasudevan, Cyrus DiCiccio, and Kinjal Basu At LinkedIn, our imperative is to create economic opportunity for every...
- Topics:
- Spark,
- artificial intelligence,
- machine learning,
- Data,
- Open Source