This repository contains the code and files for a book recommendation system based on machine learning. The system uses collaborative filtering techniques to recommend books to users based on their books ratings and user preferences.
To use the book recommendation system, follow these steps:
1. Clone the repository to your local machine
2. Install the required dependencies
3. Run the 'app.py' file to start the Flask application
4. Navigate to 'localhost:5000' in your web browser
5. Enter your reading history and preferences to receive book recommendations
- This dataset contains information on over thousand of books, including their titles, ISBN, authors, genres, and user ratings.
- Users = https://docs.google.com/spreadsheets/d/1edu7wtvLK9J24WfbqEBpOLNLaQPYti2WX7wkgBkuIi0/edit?usp=sharing
- Books = https://docs.google.com/spreadsheets/d/18v6VtVEO_FV6qxlwbJ31jj_qECjhAqunaRfH1UomeYc/edit?usp=sharing
- Ratings = https://docs.google.com/spreadsheets/d/1zIwlAVMyC5DUKXGehWvW-tiRW-NENg_bIcjHju-c5qU/edit?usp=sharing
This project was created by Dheeraj Kulariya. It was completed as part of Data Science at Introtallent.
The machine learning algorithm used in this project was adapted from the scikit-learn library.
To run the code in this repository, you will need the following:
- Python 3.x
- pandas
- numpy
- scikit-learn
- Flask
- pickle