Book-Recommendation-System

Check Out the Book Recommendation System Here:

BooksMate

Description:

A Book Recommendation System which recommends the users a selection of books based on their interests. It also has a separate page for the list of all books.

Data used for this project was taken from here.

1. Data Cleaning and Pre-Processing

The dataset consists of three tables; Books, Users, and Ratings. Data from all three tables are cleaned and preprocessed separately.

2. Algorithms Implemented:

2.1 Popularity Based Recommendation :

• Popular in the Whole Collection
  

We have sorted the dataset according to the total ratings each of the books have received in non-increasing order and then recommended top 50 books.

2.2 Content Based Recommendation

This system recommends books by calculating similarities in Book Titles. For this, TF-IDF feature vectors were created for unigrams and bigrams of Book-Titles; only those books' data has been considered which are having at least 50 ratings.

3. Libraries Used:

• ipython-notebook - Python Text Editor
• sklearn - Machine learning library
• numpy, scipy- number python library
• pandas - data handling library

4. Frontend

• HTML, CSS & Javascript was used for the frontend of the application.

Cooked with ♥ by WilsonVD