Machine learning is a key component of LinkedIn’s relevance-driven products. We use machine learning to train the ranking algorithms for our feed, advertising, recommender systems (such as People You May Know), email optimization, search engines, and more. For an in-depth example, check out these posts (part one and two) on how LinkedIn applies machine learning...
Relevance Science Articles
-
- Topics:
- Spark,
- Relevance Science,
- Dr. Elephant,
- Open Source,
- relevance,
- Photon ML,
- machine learning
-
LinkedIn wouldn't be the company it is today without the engineers who built it. We have no shortage of talented individuals in technical roles across the company. They are the ones who create, build, and maintain our platform, tools, and features—as well as write posts for this blog. In this series, we feature some of the people and personalities that make...
- Topics:
- relevance,
- engineering culture,
- Relevance Science
-
I get asked a lot of questions by my friends about relevance science and engineering at LinkedIn. Why has relevance science become so important in the Internet industry? What does being a relevance engineer mean at LinkedIn? What relevance products are we building? How are we building those? What are the skills required to build those? And most of all, how does...
- Topics:
- relevance,
- engineering culture,
- Hiring,
- Relevance Science