Quick answer: Personalization + ranking — the foundation of Flipkart, Swiggy, Zomato, Myntra.
Recommendation Systems are algorithms that predict what users want before they ask for it. They analyze user behavior, preferences, and patterns to suggest products, content, or services tailored to individual tastes. Whether it's "Customers who bought X also bought Y" on Flipkart, personalized food delivery rankings on Swiggy, or curated restaurant feeds on Zomato, recommendation systems power the discovery layer of modern applications.
At their core, they solve a fundamental problem: with millions of items available, how do you surface the few that matter most to each user? You'll work with collaborative filtering (finding similar users), content-based approaches (matching item features), and hybrid methods combining both. These systems directly impact user engagement, revenue, and retention—making them critical infrastructure for any platform handling choice at scale.