Introduction
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.
Goal:
In this project we are going to build recommendation model for the electronics products of Amazon. Attribute Information: userId : Every user identified with a unique id (First Column) productId : Every product identified with a unique id(Second Column) Rating : Rating of the corresponding product by the corresponding user(Third Column) timestamp : Time of the rating ( Fourth Column)