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...
machine learning Articles
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Co-authors: Jun Jia and Alice Wu Introduction It’s a very common scenario that an AI solution involves composing different jobs, such as data processing and model training or evaluation, into workflows and then submitting them to an orchestration engine for execution. At large companies such as LinkedIn, there may be hundreds of thousands of such executions per...
- Topics:
- Python,
- machine learning,
- Open Source
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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...
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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...