At LinkedIn, most decisions are made using experiments. When we want to decide between two features, we test them against each other in the real world: we give feature A to a random set of members, feature B to another set, and we compare the results. Are users of feature A more engaged? Do they have a better experience with our products? If so, feature A wins....
data science Articles
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- Topics:
- A/B Testing,
- Testing,
- data science,
- experimentation,
- T-REX,
- Data
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LinkedIn wouldn't be the company it is today without the engineers who built it and the 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 LinkedIn great....
- Topics:
- data science,
- culture
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Co-authors: Burcu Baran, Xiaojing Dong, Chi-Yi Kuan, Emily Huang, and Tiger Zhang At LinkedIn, we have more than 630M members, 30M companies, and 90K schools on our platform. As the largest professional network, LinkedIn transforms companies by changing the way they hire, market, sell, and work. Members use LinkedIn to connect with other professionals, expand...
- Topics:
- data science,
- machine learning,
- metrics,
- Data,
- events
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Co-authors: Bonnie Barrilleaux and Dylan Wang Our 567M members use the LinkedIn feed to talk to each other a lot: more than a million...
- Topics:
- Feed Personalization ,
- A/B Testing,
- data science,
- experimentation,
- Data,
- relevance,
- T-REX
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I’m sure everyone who has been following tech industry news knows about “big data” and “AI.” Although there is no industry-consistent...
- Topics:
- Craftsmanship,
- data science,
- machine learning,
- Analytics,
- Data
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In a previous post, I gave some advice for those who are interested in a career in data science. One of the suggestions I made was to...
- Topics:
- data science,
- engineering culture