Co-authors: Madhumita Mantri and Tyler James At LinkedIn, ThirdEye is used for business and platform health metrics monitoring, keeping track of a variety of metrics across production infrastructure, AI model performance, or key business indicators (i.e., page view or click count). It’s a key quality assurance system for two reasons: its rule- or model-based...
machine learning Articles
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- Topics:
- artificial intelligence,
- monitoring,
- Pinot,
- machine learning,
- metrics,
- Data
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Co-authors: Guillaume Saint-Jacques, Stuart Ambler Last month on this blog, we introduced how we are building inclusive products through A/B testing, something we internally call Project Every Member, and discussed the novel application of inequality A/B testing using the Atkinson index and the use of this technique in the product design process at LinkedIn....
- Topics:
- data science,
- experimentation,
- machine learning,
- research,
- Product Design,
- Data
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Co-authors: Siddharth Dangi, Johnson Jia, Manas Somaiya, and Ying Xuan The LinkedIn feed is the cornerstone of the member experience. It’s where our members post ideas, career news, questions, and jobs in an array of formats, including short text, long-form articles, images, and videos. The Feed AI Team’s mission is to help LinkedIn’s members discover the most...
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Co-authors: Jun Shi, Mingzhou Zhou Introduction In the machine learning community, Apache Spark is widely used for data processing due...
- Topics:
- Spark,
- machine learning,
- TensorFlow,
- Data,
- Open Source
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Serving the most relevant information for LinkedIn members in the homepage feed requires a massive effort—hundreds of features are...
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Co-authors: Guillaume Saint-Jacques, Amir Sepehri, Nicole Li, and Igor Perisic Introduction Previously on this blog, we’ve shared...
- Topics:
- A/B Testing,
- data science,
- experimentation,
- research,
- Product Design,
- Data,
- machine learning,
- T-REX