📚 Building a Book Recommendation System with Streamlit & Collaborative Filtering
Recommendation systems are used in many of the apps we use every day – from Netflix suggesting movies to Amazon recommending products . As a book lover and data science enthusiast , I wanted to create a system that helps readers find new books based on what they like . In this post , I’ll walk you through how I built a Book Recommendation System using Python , Streamlit , and Collaborative Filtering . 📌 Project Overview The goal was to create a simple yet effective web app that: * Shows the Top 50 most popular books based on average ratings. * Recommends similar books to a user - selected title using collaborative filtering. * Provides a clean , interactive user interface built with Streamlit. 📁 Dataset I used the Book Recommendation Dataset from Kaggle, which includes : * Books.csv – Book details like title , author , and image URL * Users.csv – User demographic data * Ratings .csv – Book rat...