Abstract

Nowadays, with so many films, web series, and TV shows available on digital platforms, it may be exceedingly difficult for consumers to sift through the large library of content and discover something that suits their tastes and preferences. "Cine Sense," a movie recommendation system, stands at the forefront of this transformative endeavour. Modern machine learning techniques are skilfully integrated into "Cine Sense" to form its basis. A unique cinematic experience is guaranteed by the system's ability to recognize user behaviour, preferences, and viewing habits to provide customized learning routes and real-time feedback systems. It represents a harmonious blend of entertainment technology, machine learning, and modern web development principles. React JS, CSS, and Tailwind CSS is used for creating a visually appealing and user-friendly interface. TMDB (The Movie Database) API (Application Programming Interfaces) for accessing a vast repository of movie and TV show information. Machine learning models will be integrated for personalized content recommendations based on user behaviour and preferences.