Book Recommendation System

This project was made using the concept of Collaborative Filtering in python to recommend books relevant to the product search which the user performs.

Dataset Used

Kaggle book dataset: https://www.kaggle.com/datasets/arashnic/book-recommendation-dataset

Collaborative filtering

In Collaborative Filtering, we tend to find similar users and recommend what similar users like. In this type of recommendation system, we don’t use the features of the item to recommend it, rather we classify the users into the clusters of similar types, and recommend each user according to the preference of its cluster. To find the similarity of books and recommend them to user, I have used the following parameters for cosine similarity:

1. Only the ratings from users who have rated more than 200 books have been counted.
2. Minimum rating for a book to be recommended is by atleast 50 users.

Languages/Concepts used:

1. Python
2. Basic HTML
3. Basic CSS
4. Basic Bootstrap
5. Concepts of ML