BookBuddy is a web application designed to offer personalized book recommendations to users based on their reading history, preferences, and ratings. Leveraging machine learning algorithms, BookBuddy analyzes user data to provide tailored suggestions, fostering a dynamic reading experience. In addition to recommendations, the platform facilitates community engagement, tracking reading progress, and setting goals.

• Front-end: React, HTML, CSS, JavaScript
• Back-end: Python, FastAPI, Flask
• Machine Learning: scikit-learn, TensorFlow, or other ML libraries
• Database: PostgreSQL or MongoDB
• Authentication: JWT (JSON Web Tokens)
• Deployment: Docker, Kubernetes, or cloud platforms (AWS, Google Cloud, Heroku)

1. User Registration and Authentication: Secure account creation and management.
2. Reading History and Preferences: Input reading history, rate books, specify preferences.
3. Book Recommendation Engine: ML-driven personalized recommendations.
4. Reading Tracker: Track progress, set goals, manage reading lists.
5. Book Details and Reviews: Detailed book information and user reviews.
6. Community and Social Features: Connect with readers, join discussions, share recommendations.
7. Responsive Design: Optimized for various devices.

1. Planning and Design: Define scope, wireframe UI, create roadmap.
2. Front-end Development: Build UI with React, implement functionality.
3. Back-end Development: Set up server, define API endpoints, integrate ML model.
4. Database Integration: Design schema, store user data and recommendations.
5. Authentication and Authorization: Implement secure JWT-based authentication.
6. Machine Learning Model: Train and integrate recommendation model.
7. Testing and Debugging: Thorough testing, bug resolution, performance optimization.
8. Deployment: Deploy on cloud platforms or containerized environment.
9. Continuous Integration and Deployment: CI/CD pipeline for automated testing and deployment.
10. Documentation and Maintenance: Codebase documentation, user guides, ongoing maintenance.