Book Recommendation System
Looking for a smart, AI-powered book recommendation engine for your application or portfolio? Presenting a professionally developed Book Recommendation System using modern machine learning tools and APIs. This project is ideal for developers, startups, and students seeking a ready-to-integrate solution for book suggestions based on user preferences.
🔧 Project Summary
| Project Name | Language Used | Developer | Type |
|---|---|---|---|
| Book Recommendation System | Python | UPDATEGADH | Web Application |
💡 Project Description
This intelligent system recommends books similar to the one selected by a user. Built on top of a precomputed similarity matrix and book metadata, it dynamically fetches book cover images using the Open Library API. The model files are optimized for quick loading from Google Drive using gdown.
Users get a seamless experience with an interactive frontend built using Streamlit – perfect for instant deployments and demonstrations.
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🚀 Available Features
- 🔍 Search and select a favorite book from the list
- 📚 Get up to 20 AI-recommended similar books
- 🖼️ View dynamically fetched book cover images using the Open Library API
- ⚡ Fast performance with precomputed
.pklmodel files - ☁️ Google Drive integration for remote file loading
- 🔐 Secure secret management via
.streamlit/secrets.toml
🛠️ Tech Stack
- Language: Python
- Framework: Streamlit
- Libraries:
pandas,pickle,gdown - External API: Open Library API
- Cloud Storage: Google Drive for
.pklmodel files - Database: ❌ No database used (Data is handled using
.pklfiles)
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