AI-Based Recommendation System

AI-Based Recommendation System

Naba Khan

Bachelor of Vocational in  of Artificial Intelligence & Data Science

Abdul Razzak Kalsekar Polytechnic New Panvel (ARKP)

Abstract
Recommendation systems have become integral in various sectors such as e-commerce, entertainment, and education. This paper presents the design and implementation of a simple AI-based recommendation system using a content-based filtering approach. The system utilizes a dataset containing product details and computes cosine similarity to recommend relevant products. Implemented with Python and deployed through a web interface using Gradio, the model provides real-time suggestions with confidence scores. The project demonstrates the feasibility of integrating machine learning techniques with interactive user interfaces to enhance the shopping experience.

Key Words: AI, recommendation system, cosine similarity, content-based filtering, Gradio, product recommendation