https://github.com/berkayguzel06/modelbasedmovierecommendationsystem
Welcome to the Genre-Based Movie Recommendation System! This project leverages the power of Artificial Intelligence (AI) and Machine Learning (ML) to provide personalized movie recommendations based on user preferences and genres
https://github.com/berkayguzel06/modelbasedmovierecommendationsystem
ai artifical-intelligence database fastapi flask javascript machine-learning ml movie-recomendation-system movie-recommendation-app movies-app-react postgresql python react sqlalchemy tailwind tailwindcss torch warehouse
Last synced: 3 months ago
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Welcome to the Genre-Based Movie Recommendation System! This project leverages the power of Artificial Intelligence (AI) and Machine Learning (ML) to provide personalized movie recommendations based on user preferences and genres
- Host: GitHub
- URL: https://github.com/berkayguzel06/modelbasedmovierecommendationsystem
- Owner: berkayguzel06
- License: mit
- Created: 2024-12-15T16:50:33.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-27T16:17:36.000Z (over 1 year ago)
- Last Synced: 2025-03-29T18:43:25.173Z (over 1 year ago)
- Topics: ai, artifical-intelligence, database, fastapi, flask, javascript, machine-learning, ml, movie-recomendation-system, movie-recommendation-app, movies-app-react, postgresql, python, react, sqlalchemy, tailwind, tailwindcss, torch, warehouse
- Language: JavaScript
- Homepage:
- Size: 15.8 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Genre-Based Movie Recommendation System
Welcome to the Genre-Based Movie Recommendation System! This project leverages the power of Artificial Intelligence (AI) and Machine Learning (ML) to provide personalized movie recommendations based on user preferences and genres. The system is built using a modern tech stack, including Next.js for the frontend, Flask for the backend database, and FastAPI for serving ML models created with PyTorch.
## Features
- Genre-Based Recommendations: Get movie suggestions tailored to your favorite genres.
- User-Friendly Interface: A clean and intuitive frontend built with Next.js.
- Scalable Backend: Flask handles database operations, ensuring efficient data management.
- AI/ML Integration: FastAPI serves PyTorch-based models for accurate and dynamic recommendations.
## Tech Stack
- Frontend: Next.js (React-based framework)
- Backend: Flask (Python web framework)
- ML Model Serving: FastAPI (Python API framework)
- Machine Learning: PyTorch (for building and training models)
- Database: PostgreSQL
## How It Works
- User Interaction: Users interact with the frontend, selecting their preferred genres or providing feedback on movies.
- Backend Processing: Flask handles user requests, retrieves data from the database, and communicates with the FastAPI service.
- AI/ML Model: FastAPI serves the PyTorch-based recommendation model, which processes user input and generates personalized movie suggestions.
- Recommendation Delivery: The system displays the recommended movies on the frontend, providing a seamless user experience.
