📚 Smart Book Recommendation System using Python and Flask – Free Web Project
Book Recommendation System
📌 About the Project
The Book Recommendation System is a free, open-source web application that helps users find book suggestions using data-driven logic. Built using Python (Flask), it implements both popularity-based and collaborative filtering methods to recommend books intelligently.
This project is ideal for:
- 🎓 Students working on data science or machine learning projects
- 💻 Beginners exploring recommendation systems
- 📘 Developers creating portfolio projects
| Project Name | Language Used | Developer |
|---|---|---|
| Book Recommendation System | Python, HTML, CSS | UPDATEGADH |
💡 Project Summary
We worked with a dataset containing three core files:
Books.csv– Book info (title, author, year, etc.)Users.csv– User info (location, age)Ratings.csv– Book ratings by users
The recommendation system is built in four major steps:
🔹 1. Data Cleaning & Feature Engineering
- Removed missing or irrelevant values
- Extracted meaningful features for analysis
🔹 2. Popularity-Based Recommendations
- Merged book and ratings data on ISBN
- Displayed top 50 books with the highest average ratings
- Filtered books with more than 250 ratings for better reliability
🔹 3. Collaborative Filtering
- Used memory-based filtering
- Filtered active users (rated 200+ books) and popular books (rated by 50+ users)
- Applied cosine similarity for item-item matching
- Generated recommendations using similarity scores
🔹 4. Book Recommendation Function
- Accepts a book name as input
- Returns 4 similar books along with authors using a trained model
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⚙️ Technology Stack
- Language: Python
- Framework: Flask
- Front-End: HTML, CSS
- Libraries: Pandas, NumPy, Scikit-learn
- Model Storage: Pickle (
.pkl) files - Notebook for Development: Jupyter
✅ Available Features
- 🔝 Shows top-rated books based on rating count and average score
- 🧠 Recommends similar books based on item similarity
- 🔄 Uses collaborative filtering for personalized suggestions
- 💾 Lightweight – no external database required
- 📦 Includes a full development notebook and web interface
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