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Understand how platforms analyze what you like and find items with similar characteristics
Educational content slides
Pandora's Music Genome Project:
Trained musicians manually analyze every song
450 attributes measured:
Takes 20-30 minutes per song. A human listens, tags, scores.
Example for Billie Eilish: "whispered intimate vocals, minimal instrumentation, dark pop production, unconventional song structure"
This is content-based filtering: analyzing the THING itself, not user behavior.
Pandora recommends obscure indie artists you've never heard of, while Spotify mostly suggests popular artists. Why the difference?
Complete this exercise and get AI-powered feedback.
Content-based filtering excels at niche interests where user data is sparse.
Your task: Define features for something you're passionate about, then use those features to make predictions.
This reveals: How feature selection determines recommendation quality. Good features = good recommendations.