This is a project provided by Free Code Camp.

In this model, we were able to provide recommendation of 5 books present in the dataset if provided any book from the same.

To build the model, I took reference from multiple sites and project of fellow peers.

Learning site : https://www.freecodecamp.org/learn/machine-learning-with-python/

In this challenge, you will create a book recommendation algorithm using K-Nearest Neighbors.

You will use the Book-Crossings dataset. This dataset contains 1.1 million ratings (scale of 1-10) of 270,000 books by 90,000 users.

Problem Link : https://colab.research.google.com/github/freeCodeCamp/boilerplate-book-recommendation-engine/blob/master/fcc_book_recommendation_knn.ipynb

https://datascienceplus.com/building-a-book-recommender-system-the-basics-knn-and-matrix-factorization/

https://aman-makwana101932.medium.com/understanding-recommendation-system-and-knn-with-project-book-recommendation-system-c648e47ff4f6#:~:text=%20Understanding%20Recommendation%20system%20and%20KNN%20with%20project,group%20by...%205%20Implementing%20kNN.%20%20More%20

https://github.com/kvfasoulakos/Book-Recommendation-Engine-using-KNN

https://github.com/VictorSM01/fcc_book_recommendation_knn