Building an End-to-End Recommendation System

Leveraging transformer embeddings and a vector database to speed up inference

Introduction

A field of machine learning I find really interesting is: personalising a user's experience through recommended products or services. To pursue this passion, I decided to work on an end-to-end project, starting from web scraping to building a recommender engine and, finally model deployment and monitoring.