Building a Recommendation System using Word2vec: A Unique Tutorial with Case Study in Python

Overview

  • Recommendation engines are ubiquitous nowadays and data scientists are expected to know how to build one
  • Word2vec is an ultra-popular word embeddings used for performing a variety of NLP tasks
  • We will use word2vec to build our own recommendation system. Curious how NLP and recommendation engines combine? Let’s find out!

 

Introduction

Be honest – how many times have you used the ‘Recommended for you’ section on Amazon? Ever since I found out a few years back that machine learning powers this section – I have been hooked. I keep an eye on that section each time I log into Amazon.

There’s a reason companies like Netflix, Google, Amazon, Flipkart, etc. spend millions perfecting their recommendation engine. It is a powerful acquisition channel and enhances the customer’s experience.

Let me use a recent example to showcase their power. I went to a popular online marketplace looking for a recliner. There were hundreds of them. From Traditional two-position recliners to Push-Back Liners; from Power Lift Recliner to the

 

 

 

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