Co-authors: Eing Ong, Shannon Bain, and Daniel Qiu What is MLOps? Before we dive into our MLOps portal, let’s begin by defining MLOps (Machine Learning Operations). MLOps is about continuously running ML correctly by managing the full lifecycle (developing, improving, and maintaining) for AI models. A structured and methodical approach that starts at problem...
machine learning Articles
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Co-Authors: Alex Tsun, Bo Ling, Nikita Zhiltsov, Declan Boyd, Benjamin Le, Aman Grover, and Daniel Hewlett Introduction One major goal of the LinkedIn Talent Solutions team is to match job seekers and job posters, leading to mutually beneficial outcomes. A service that any LinkedIn member can use is JYMBII (Jobs You May Be Interested In), which uses information...
- Topics:
- machine learning
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We are open sourcing Feathr – the feature store we built to simplify machine learning (ML) feature management and improve developer productivity. At LinkedIn, dozens of applications use Feathr to define features, compute them for training, deploy them in production, and share them across teams. With Feathr, users reported significantly reduced time required to...
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Co-authors: Jilei Yang, Parvez Ahammmad, Fangfang Tan, Rodrigo Aramayo, Suvendu Jena, Jessica Li At LinkedIn, we have the opportunity...
- Topics:
- machine learning,
- artificial intelligence
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Co-authors: Jilei Yang, Humberto Gonzalez, Parvez Ahammad In this blog post, we introduce and announce the open sourcing of the...
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Co-authors: Jaewon Yang, Minji Yoon, Sufeng Niu, Dash Shi, and Qi He Graphs are a universal way to represent relationships among...