Build a Movie Recommendation App with OpenAI
In this project, you'll develop Pop Choice, an AI-powered movie recommendation app designed to simplify the decision-making process for movie night.
Using AI embeddings, vector databases, and the OpenAI API, the app will recommend the perfect movie based on user preferences gathered through a series of open and close-ended questions. Users input their mood and preferences, and the app searches a database of movies to find the best match.
As a stretch goal, the app can be adapted for group recommendations, with each participant's preferences being taken into account. You'll build this project from scratch, using any framework you prefer, like React or vanilla JavaScript, and integrate a vector database, such as Supabase. The provided data includes movie details like title, plot, cast, and IMDb ratings.
This project emphasizes working with embeddings, querying databases, and generating personalized outputs using AI.
Watch on Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
Related AI Lessons
⚡
⚡
⚡
⚡
When Should You Use Text2Cypher in a GraphRAG Pipeline
Dev.to AI
How to build a production RAG pipeline in Python (without a vector database)
Dev.to · Ayi NEDJIMI
Architecting Sub-150ms Hybrid RAG for Voice Agents: Combining pgvector, BM25, and Async FastAPI…
Medium · Python
Security Controls in Enterprise RAG: Keys, Audit Logs, and the Hierarchy That Prevents Role Elevation
Dev.to · Manjunath
🎓
Tutor Explanation
DeepCamp AI