This Is How Netflix Decides What You Watch Next - Recommender System Explained

Opening your app and seeing the “perfect” movie is not magic — it’s math, data, and logic working together.

In this final video of the Recommendation System playlist, I walk through how the recommendation engine actually works end-to-end.

We connect everything together:
• User ratings
• Movie similarity calculations
• Item-Based Collaborative Filtering
• How recommendations are generated (not random!)

I demonstrate the full flow using my own Android + Spring Boot movie app powered by the TMDB API — showing how real apps think under the hood.

This video focuses on logic and problem-solving, not frameworks.

🔗 Full source code available on GitHub:
Backend: https://github.com/ShimaaAboelmagd257/IBCF-Recommender
frontend -Android : https://github.com/ShimaaAboelmagd257/Recs-Android/tree/master

#RecommendationSystem #BackendEngineering #SystemDesign
#Algorithms #CollaborativeFiltering #AndroidDevelopment #SpringBoot #SoftwareEngineering #HowAppsWork
#ProgrammingConcepts #android #education

Видео This Is How Netflix Decides What You Watch Next - Recommender System Explained канала Exceptions with Shimaa