📚 Book Recommender System

The Book Recommender System project is developed with the goal of applying Machine Learning techniques to build an intelligent book recommendation system.

The system supports three main recommendation methods: 1️⃣ Item-based Collaborative Filtering — recommends books based on user rating behavior. 2️⃣ Content-based Filtering — recommends books based on book content (title + author). 3️⃣ Clustering-based Recommendation — recommends books from similar user or item clusters.

Interface Deployment: The application interface is built with Streamlit, allowing users to easily select a recommendation method and receive book suggestions.

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HOW TO RUN:

Run virtual environment

.conda activate ./env

Install dependencies

pip install -r requirements.txt

Run in Notebook in Anaconda (optional)

jupyter notebook

Run Web App

streamlit run app.py

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Push an existing repository from the command line git remote add origin https://github.com/puonghoccode/Book-Recomender-System-Machine-Learning.git git branch -M main git push -u origin main