Recommendation System For Products

The retail industry's digital transformation has accelerated the need for personalized shopping experiences to enhance customer satisfaction and drive sales. Recommendation systems play a crucial role in achieving this by suggesting relevant products based on user data. This project focuses on developing a recommendation system for Escape Closet, a fictional clothing brand, aiming to improve product discovery and boost sales. By leveraging collaborative filtering and content-based filtering, the system will analyze user behavior, preferences, and product attributes. The integration of these techniques ensures more accurate and relevant suggestions. Ultimately, the system enhances customer engagement through tailored recommendations.