Build a Basic Recommendation System in 3 Lessons

Concept

Recommendation systems influence everything from online shopping to streaming suggestions. At their core, they predict what you might like based on past behavior. ## Types of Recommendation Systems Broadly, there are collaborative filtering and content-based systems. Collaborative filtering uses user interaction data, like ratings or clicks, to recommend items. Content-based filtering suggests items similar to those a user has liked in the past. Hybrid models combine both approaches. ## Real-world Applications Amazon's 'Customers who bought this also bought' is a classic example of collaborative filtering. Spotify's 'Discover Weekly' uses a blend of collaborative and content-based methods to curate playlists.