Book Recommender System 📚

Description

This project implements a Book Recommender System using Streamlit, where users can explore popular books, get recommendations based on book similarity scores using collaborative filtering, and manage their "To Read" list.

Features

• Home Page:

  • Displays popular books based on average ratings from users who rated more than 250 books.
  • Allows users to add books to their "To Read" list.

• Recommendation Page:

  • Users can select a book and get recommendations based on similarity scores with other books in the dataset using collaborative filtering.
  • Top 4 most similar books are recommended.

• To Read List:

  • Displays the list of books added by the user to read.
  • Allows users to mark books as read/unread.

Popularity-Based System

• The Home Page showcases popular books based on average ratings from users who have rated more than 250 books. The top 100 most popular books are displayed.

Collaborative Filtering

• The Recommendation Page utilizes collaborative filtering to recommend books based on similarity scores between books. It calculates the similarity between selected books and suggests the top 4 most similar books.

Setup Instructions

1. Clone the Repository:

   git clone https://github.com/your_username/book-recommender-system.git
   cd book-recommender-system

2. Install Dependencies:

   pip install -r requirements.txt

3. Run the Application:

   streamlit run app.py
   

Here's how it turned out: