ML Unsupervised Learning: Book Recommendation System
Welcome to the ML Unsupervised Learning Book Recommendation System repository! This project aims to build a recommendation system for books using unsupervised machine learning techniques.
Introduction
In this repository, you'll find code and resources to implement a book recommendation system using unsupervised learning algorithms. The recommendation system suggests books to users based on their preferences and behavior, without the need for explicit ratings or labels.
Features
Unsupervised Learning Techniques: Utilizes clustering algorithms such as k-means or hierarchical clustering to group similar books and users.
Data Preprocessing: Includes data cleaning, transformation, and feature engineering to prepare the dataset for modeling.
Scalability: Designed to handle large volumes of data efficiently, ensuring scalability as the user and book database grows.
Getting Started Prerequisites Python 3.x Required libraries (specified in requirements.txt)