1-Introduction

Recommendation systems have been around with us for a while now, and they are so powerful. They do have a strong influence on our decisions these days. From movie streaming services to online shopping stores, they are almost everywhere we look[1].

We may look very different from each other, but our habits can be very similar. And the companies love to find similar habits of their customers. Since they know that many people who bought “x” item also bought “y” item, they recommend you to add “y” item to your cart. And guess what, you are training your own recommender the more you buy, which means the machine will know more about you[1].

Recommendation systems are among the most popular applications of data science. They are used to predict the Rating or Preference that a user would give to an item[2].

Almost every major company has applied them in some form or the other: Amazon uses it to suggest products to customers, YouTube uses it to decide which video to play next on auto play, and Facebook uses it to recommend pages to like and people to follow[2]