README.md

metadata

license: mit
title: book_recomender
sdk: gradio
emoji: 🐨
colorFrom: yellow
colorTo: yellow
pinned: true
short_description: book recommnedation

Content-Based Book Recommender System

This project provides a modular implementation of a content-based book recommendation system using Python. It uses TF-IDF vectorization and cosine similarity to recommend books based on their summaries.

Features

• Load and preprocess datasets
• Compute similarity between books based on their summaries
• Generate content-based recommendations

Files

• app.py: Entry UI for the recommendation system
• data_loader.py: Handles data loading and preprocessing
• recommender.py: Core recommendation logic
• requirements.txt: Lists dependencies

Dependencies

• pandas: For data manipulation
• scikit-learn: For TF-IDF vectorization and cosine similarity calculation

Usage

1. Install dependencies:

   pip install -r requirements.txt