Abstract:
Product Recommendation System Using ML In today’s modern epoch of information
technology, the idea of efficiently finding one’s favourite product in a large dataset of
application database, becomes an essential issue to address for the online content providers in
order to attract the masses as opposed to their competitors. Recommender systems or recommendation
systems, as they are popularly known, are information filtering systems which are
usually integrated with several consumer and com- mercial applications. Such systems act as
a bridge between various content facilitators such as social media websites, e-commerce portals,
streaming platforms, etc. and the users of these applications, by suggesting them items
from the application database which conform to the user preferences and past activities. Such
personalized systems play a vital role, especially when the user is unclear of the item to the
searched for. These systems are infiltrating every aspect of our lives, in the form of ?Because
you watched? header on Netflix, ?People you may know? section on Facebook, ?Customers
who bought this also bought’ partition on Amazon.
