Collaborative filtering machine learning models

Abstract

This paper provides an overview of collaborative filtering machine learning models, tracing their history, explaining their fundamentals, and discussing their strengths and limitations. Collaborative filtering is a popular technique in recommendation systems, which leverages user behavior data to make predictions and generate personalized recommendations. I will explore the evolution of collaborative filtering models over the years and highlight key advancements. This paper aims to provide a comprehensive history and understanding of collaborative filtering models and their impact on personalized recommendation systems. The reason I am speaking about collaborative filtering models is because it was the method used to build two of the main models for my Data Science Capstone Project.