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Collaborative Filtering: What Similar Users Liked

Discover how platforms find people like you and recommend what they enjoyed

Part of How Netflix, Spotify, TikTok Know You

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Last updated Oct 29, 2025. Clone to remix or explore the blocks below.
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content

The $1 Million Netflix Discovery

Educational content slides

The $1 Million Netflix Discovery

2006: Netflix offers $1 million prize to improve recommendations by 10%

The winning insight: Don't analyze movies. Analyze PEOPLE.

"People who liked what you liked also enjoyed..."

This single idea revolutionized recommendations. Instead of understanding why you like Attack on Titan (complex plot, dark themes, action), the algorithm finds people with similar taste patterns and recommends what they watched.

No content analysis needed. Just behavior patterns.

This is collaborative filtering—and it changed everything.

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quiz

Quiz: 3 Questions

Test your understanding with this quiz.

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You just created a Netflix account. Why does it show 'Trending Now' instead of personalized recommendations?

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feedback

Apply Collaborative Filtering

Complete this exercise and get AI-powered feedback.

Apply Collaborative Filtering

Collaborative filtering finds patterns in collective behavior. Where could this help in your life?

Think about: Any situation where 'people like you' is a useful signal—classes, food, events, content, purchases.

Key insight: You don't need to understand why similar people like something, just that they do.