Book Recommendation Engine

Tooling Used

• Python
  • Numpy
  • Pandas
  • Sklearn

Concepts Used

• KNN
• Collaborative Filtering

Collaborative Filtering

The simplest and original implementation of this approach recommends to the active user the items that other users with similar tastes liked in the past. The similarity in taste of two users is calculated based on the similarity in the rating history of the users. This is the reason why refers to collaborative filtering as “people-to-people correlation.”

In this notebook I have implemented a collaborative Filtering technique for recommendation of books. The Dataset provided has been preprocessed and techniques and filters applied are discussed briefly.