Eugene Yan • 2/26/2023

Content Moderation & Fraud Detection - Patterns in Industry

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This technical article analyzes industry practices for content moderation and fraud detection. It details five key patterns: collecting ground truth via human-in-the-loop, data augmentation, using a cascade pattern, combining supervised and unsupervised ML, and ensuring model explainability. It references real-world implementations from companies like Stack Exchange, LinkedIn, Uber, Meta, and DoorDash.

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#Machine Learning #content moderation #Supervised Learning
Content Moderation & Fraud Detection - Patterns in Industry

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