MOVIE SUGGESTION SYSTEM USING MACHINE LEARNING TECHNIQUES

MOVIE SUGGESTION SYSTEM USING MACHINE LEARNING TECHNIQUES

 Byreddy Vinay Reddy1, Gagan Guptha2 , Gajji Shiva3,  Guduru Rajesh Reddy4,

N. Selvamuthukumaran5

 1,2,3,4B.Tech. Student, Department of Computer Science and Engineering,

vinayreddybyreddy@gmail.com, guptagagan449@gmail.com, shiva13817@gmail.com,

gudururajeshreddy@gmail.com, selvamuthukumaran.cse@nmrec.edu.in

5Assistant Professor, Department of Computer Science and Engineering,

Nalla Malla Reddy Engineering College, Hyderabad, India

Abstract—

Movie suggestion systems have gained significant popularity in recent years, as people increasingly seek personalized recommendations for their viewing choices. To provide these recommendations, machine learning algorithms are widely used. These systems analyse the user's viewing history, ratings, and reviews, using techniques such as collaborative filtering, content-based filtering, and hybrid models. With the use of big data, these systems have become more accurate and efficient, providing users with a better movie watching experience. By leveraging machine learning techniques, movie suggestion systems are able to deliver relevant and precise recommendations to individual users, making the overall movie watching experience more enjoyable and satisfying.

Keywords— Genre, Plot, Cast, Director, Similar movies, User preferences, Streaming platforms