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...
Data Articles
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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 to its efficiency in SQL-style operations, while TensorFlow is one of the most popular frameworks for model training. Although there are some data formats supported by both tools, TFRecord—the data format native to TensorFlow—is...
- Topics:
- Spark,
- machine learning,
- TensorFlow,
- Data,
- Open Source
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Built at LinkedIn, Pinot is an open source, distributed, and scalable OLAP data store that we use as our de-facto near-real-time analytics service. We’ve previously discussed how and why we built Pinot to power a wide spectrum of use cases, including internal business intelligence dashboards to analyze highly-dimensional data and “Who Viewed My Profile” to...
- Topics:
- Pinot,
- metrics,
- 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
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Co-authors: Walaa Eldin Moustafa, Wenye Zhang, Adwait Tumbde, Ratandeep Ratti Introduction Over the years, the popularity of Apache...