Lesson 098 chapters~2 min

Recommendation Systems and Learned Attention

Recommendation systems turn behavior into a continuously updated model of what to show next. Their objective function determines both product performance and product consequences.

Learning outcomes
  • Separate social-graph, interest-graph, collaborative, semantic, and content-based signals
  • Explain exploration versus exploitation
  • Choose objectives beyond raw engagement
Field assignment

For a feed you know, list candidate signals, their probable weights, the optimization target, cold-start strategy, exploration budget, and one quality counter-metric.

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All 8 chapters open with the Basic or Advanced edition.

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Lesson 9: Recommendation Systems and Learned Attention — InnerPing