Building recommendation system for products on an e-commerce website like Amazon.com.
Online E-commerce websites like Amazon, Filpkart uses different recommendation models to provide different suggestions to different users. Amazon currently uses item-to-item collaborative filtering, which scales to massive data sets and produces high-quality recommendations in real time. This type of filtering matches each of the user's purchased and rated items to similar items, then combines those similar items into a recommendation list for the user. In this project we are going to build recommendation model for the electronics products of Amazon.
The dataset here is taken from the below website:-
Source - Amazon Reviews data (http://jmcauley.ucsd.edu/data/amazon/) The repository has several datasets. For this case study, we are using the Electronics dataset.