Where this shows up

You don't have to look far for recommender systems — you're marinating in them. The score-and-rank machine from this course is running every time you open an app, quietly deciding what billions of people see next.

Here's where it shapes your day.

The same idea, many jobs

Every one is the ranking loop you built:

• Learn a taste profile from implicit signals, then score candidates and show the top few.
• Feeds, streaming and shopping differ mainly in the items and the signals — collaborative filtering and taste vectors under the hood.
• Ads are recommendations where the "engagement" being predicted is a click that someone pays for.
• All of them wrestle with cold start and the feedback loops that create filter bubbles.

Worth staying aware of

Because these systems optimize for engagement, they can amplify outrage, narrow what you see, and shape behavior in ways that aren't always in your interest. Knowing how the machine works is what lets you notice when your feed is steering you.

That's the course

You now know what's behind the feed: it's a ranking of scored candidates, built from your taps, people like you, taste vectors, and the loop you're part of.

If you enjoyed this, the other courses cover the embeddings and models these systems are built on.