Co-authors: Preetam Nandy, Yunsong Meng, Cyrus DiCiccio, Heloise Logan, Amir Sepehri, Divya Venugopalan, Kinjal Basu, and Noureddine El Karoui Introduction LinkedIn’s vision to create economic opportunity for every member of the global workforce would be impossible to realize without leveraging AI at scale. We use AI in our core product offerings to: highlight...
artificial intelligence Articles
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In recent years, we’ve been fortunate to see a growing number of excellent machine learning tools, such as TensorFlow, PyTorch, DeepLearning4J, and CNTK for neural networks, Spark and Kubeflow for very-large-scale pipelines, and scikit-learn, ML.NET, and the recent Tribuo for a wide variety of common models. However, models are typically part of an integrated...
- Topics:
- machine learning,
- artificial intelligence,
- Data
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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...
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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...
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Our logo is inspired by the chameleon: You can enable personalization on your ranking model with GDMix, bringing a personalized...
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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