What is collaborative filtering in AI recommendation engines?

What is collaborative filtering in AI recommendation engines?

Collaborative filtering is a technique used in recommendation systems that predicts user preferences based on past behaviors and preferences of similar users.

How does it differ from content-based filtering?

While collaborative filtering relies on user interactions and similarities, content-based filtering recommends items based on the features of the items themselves.

Can you give me an example of collaborative filtering in action?

Sure! A common example is Netflix, which recommends shows based on what similar users have watched and enjoyed.

What are the challenges of using collaborative filtering?

Some challenges include the cold start problem, where new users or items lack sufficient data, and scalability issues with large datasets.