Co-authors: Sneha Chaudhari, Mahesh Joshi, and Gungor Polatkan In part 1 of this series, we shared a high-level overview of our course recommendation engine for LinkedIn Learning. First, we provided details on the offline and online components of the system design. Later on, we discussed the three main components of the recommendation engine that are key for...
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Co-authors: Timothy Santos and Jeremy Lwanga LinkedIn is a mission-driven organization, and we take our mission of “connecting the world's professionals to make them more productive and successful” very seriously. One way we’ve worked toward this goal is through LinkedIn Talent Insights, which first launched in 2018. This is a tool that helps organizations...
- Topics:
- Pinot,
- Product Design
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Introduction When testing Android applications (for example, the LinkedIn mobile app for Android), thorough testing practices can easily lead to a growth in the number of overall tests being performed—from hundreds to thousands to even tens of thousands. Clearly, there is a need to scale significantly, while at the same time keeping test run times reasonably...
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Co-authors: Madhumita Mantri and Tyler James At LinkedIn, ThirdEye is used for business and platform health metrics monitoring,...
- Topics:
- artificial intelligence,
- monitoring,
- Pinot,
- machine learning,
- metrics,
- Data
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Espresso is LinkedIn's defacto NoSQL database solution. It is an online, distributed, fault-tolerant database that powers most of...
- Topics:
- Performance,
- ESPRESSO,
- site speed,
- SRE
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Co-authors: Sneha Chaudhari, Mahesh Joshi, and Gungor Polatkan LinkedIn Learning is a platform where LinkedIn members have the...