Movie Recommendation System Using Machine Learning

Abstract-- The recommendation system of today helps users locate the items which they need most. Movie The purpose of recommendation systems is to guide movie enthusiasts toward selecting their next movie view A large number of movies that might take considerable time to select can be bypassed through this system. The process requires substantial time along with causing confusion from several thousands or millions of options. This paper seeks to decrease the need for human involvement. A suggestion system cuts down human work by recommending movies that match user preferences. To handle such problems, we the proposed model united elements from both content-based and collaborative filtering systems. It will give This system delivers better outcome clarity when compared to content-based systems established previously. approach. Content-based recommendation systems function for people only and therefore they limit users to specific choices. The prescriptions from this system exist outside common recommendations which prevents users from expanding their discovery potential. Hence, we have focused Our system aims to address and solve the identified problems.