AI-Based Movie Recommendation System
Bui lt a full-stack movie recommendation platform with phone-based OTP login, user profiles, watched movie lists, and personalized movie
suggestions. Designed PostgreSQL tables for users, profiles, OTP, movies, genres, directors, watched movies, refresh tokens, and
recommendations using Prisma ORM. Implemented secure login with hashed OTP codes, JWT access tokens, Redis-backed sessions, logout
session invalidation, and refresh token revocation. Imported a 500-movie catalog with IMDb metadata and poster URLs, plus search, genre
filtering, movie details, and paginated list views. Created a content-based recommendation engine that scores movies from watched history
using genre matches, directors, ratings, popularity, and release-year signals. Integrated RabbitMQ-ready recommendation jobs, structured
API success/failure responses, centralized logging, and a responsive React UI.
Technologies: TypeScript, React, Node.js, Express.js, PostgreSQL, Prisma, Redis, RabbitMQ, JWT, Docker, REST API
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