Thesis Abstract

This project aims to develop a recommendation system that leverages machine learning algorithms to deliver personalized content to users based on their preferences, behavior, and historical interactions. The system will utilize collaborative filtering, content-based filtering, and hybrid recommendation techniques to provide accurate and relevant suggestions across various domains such as e-commerce, entertainment, and news. The project will focus on algorithmic efficiency, scalability, and user satisfaction to enhance the overall content delivery experience.

Thesis Overview