Brec
Brec is a production-grade book recommendation engine that delivers personalized book suggestions using advanced machine learning techniques and efficient similarity search algorithms.
Overview
Built to handle over 1 million ratings, Brec provides real-time personalized book recommendations through a sophisticated collaborative filtering system enhanced with FAISS for fast similarity search.
Technical Stack
- Backend: Python, Flask
- Frontend: Next.js, Tailwind CSS
- ML Engine: Collaborative Filtering, FAISS
- Caching: Redis
Key Features
- Real-time personalized recommendations based on user preferences
- Fast similarity search using FAISS for scalable performance
- Redis caching layer for optimized response times
- Interactive user interface with book selection and recommendations
- Integration with Goodreads for additional book information
Performance Optimizations
The system addresses performance challenges through:
- FAISS integration for efficient nearest neighbor search
- Redis caching for frequently accessed data
- Optimized Pandas operations for data processing
- Dockerized deployment for consistent environments
For a detailed breakdown of the development process, challenges faced, and lessons learned, check out my blog post about Brec.