📚 Book Recommendation API

1. Overview

A Django REST API for managing a personal book library and getting machine‑learning‑based recommendations.
Users can add books, rate them, search, and get tailored recommendations powered by a KMeans clustering model trained on 5,000 users. The repository for the Machine-Learning Model can be found here: https://github.com/Jason-Govender/ML-Book-Recommender

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2. Features

• ➕ Add a book
• ❌ Remove a book
• 🔍 Search for books
• ⭐ Rate a book
• 🗑 Remove a rating
• 📄 List all books
• 📊 List all ratings
• 🤖 Recommend books based on similar users’ reading patterns

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3. Tech Stack

• Backend: Django REST Framework
• Database: SQLite
• Machine Learning: scikit‑learn (KMeans clustering, StandardScaler)
• Language: Python 3.13

4. API Endpoints

Method	Endpoint	Description
POST	/books/add/	Add a new book
GET	/books/	List all books
DELETE	/books/<pk>/	Remove a specific book
GET	/books/search/?q=<term>	Search for books
POST	/ratings/add/	Add a rating
DELETE	/ratings/<pk>/	Remove a rating
GET	/ratings/	List all ratings
GET	/recommend/	Get book recommendations

6. Machine Learning

• Algorithm: KMeans clustering
• Clusters: 50
• Dataset: 5,000 users
• Preprocessing: StandardScaler for feature normalization
• Logic:
  • Assigns each user to a cluster based on their ratings.
  • Recommendations are drawn from the top‑rated books in the user’s cluster.