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How Pinterest Uses Crystal

7 engineering articles about Crystal from Pinterest's engineering team

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Pinterest
Intermediate
The article discusses Non-Engagement Signals, which are essential for platforms like Pinterest to avoid optimizing for low-quality content driven by user engagement.
Pinterest Engineering
9 min read
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Pinterest
Beginner
The article discusses how Pinterest developed its Trust & Safety team to combat spam and unsafe content.
Pinterest Engineering
10 min read
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Pinterest
Intermediate
This article discusses the transition from a single-output deep neural network to a multi-task learning (MTL) framework for home feed ranking at Pinterest.
Pinterest Engineering
12 min read
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Pinterest
Intermediate
This article discusses how Pinterest utilizes AutoML, Multi-task Learning, and Multi-tower models to enhance its Ads marketplace.
Pinterest Engineering
13 min read
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Pinterest
Intermediate
The article discusses the development of a real-time user signal service at Pinterest that enhances feature engineering for personalized content delivery.
Pinterest Engineering
8 min read
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Pinterest
Beginner
The article discusses the improvements made to the Related Pins feature on Pinterest, focusing on addressing the cold start problem to enhance the freshness and relevance of recommendations.
Pinterest Engineering
5 min read
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Pinterest
Intermediate
The article discusses how Pinterest utilized machine learning to enhance user engagement globally, particularly through improvements in the home feed experience.
Pinterest Engineering
7 min read
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