Co-authors: Rupesh Gupta and Lingjie Weng LinkedIn’s mission is to connect the world’s professionals to make them more productive and successful. Becoming more productive and successful is a lifelong journey. In this journey, members leverage LinkedIn in different ways, such as to build their professional networks, learn new skills, showcase their profiles, find...
machine learning Articles
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- Topics:
- artificial intelligence,
- machine learning
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Co-authors: Ian Ackerman and Saurabh Kataria Editor’s Note: Multi-objective optimization (MOO) is used for many products at LinkedIn (such as the homepage feed) to help balance different behaviors in our ecosystem. There are two parts to how we work with multiple objectives: the first is about training high-fidelity models to predict member behavior (e.g.,...
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Co-authors: Reza Hosseini, Albert Chen, Kaixu Yang, Sayan Patra, Rachit Arora, and Parvez Ahammad In this blog post, we introduce the Greykite library, an open source Python library developed to support LinkedIn’s forecasting needs. Its main forecasting algorithm, called Silverkite, is fast, accurate, and intuitive, making it suitable for interactive and...
- Topics:
- data science,
- machine learning,
- Data,
- Open Source
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Co-authors: Preetam Nandy, Yunsong Meng, Cyrus DiCiccio, Heloise Logan, Amir Sepehri, Divya Venugopalan, Kinjal Basu, and Noureddine...
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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...
- 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,...
- Topics:
- machine learning,
- artificial intelligence,
- Data