An Undergraduate Internship/Project on Book Recommendation System at ADN DigiNet

Abstract

As an intern in the artificial intelligence division of ADN DigiNet, I had the opportunity of developing prototypes and proof of concept projects utilizing Machine Learning (ML) and Artificial Intelligence (AI) techniques. The internship commenced with an intensive two- month training phase, immersing us in ML concepts, tools, and available libraries. Subsequently, the final month was dedicated to applying our newly acquired knowledge and skills to work on individual projects. The development of an intelligent book recommendation system was the main goal of my project, that utilizes AI techniques to suggest popular books to users and recommend books based on similarity. The primary objective of the system is to address the growing challenge of information overload in the digital age, where countless books are published regularly, making it increasingly difficult for users to discover relevant and interesting reads. As part of this project, I played a key role in developing the system's AI model. I was specifically in charge of putting the essential features into place, such as the collaborative and popularity-based filtering methods. Throughout the development process, various challenges were addressed, including data preprocessing and model optimization. By employing suitable AI techniques, the model successfully overcomes these challenges, resulting in an effective book recommendation system.