• Ajinkya Satuse
• Omkar Bhalerao
• Pavan Pawar
• Hrithik Thorat
• Deepali Hirolikar

A recommendation system is a system that, depending on a data set, makes recommendations to users for specific resources such as books, movies, songs, and so on. Typically, movie recommendation systems anticipate what movies a user would enjoy based on the characteristics of the User and previously provided data. Such recommendation systems are useful for businesses that collect data from a big number of clients and want to deliver the best recommendations available. Many elements can be taken into account while creating a movie recommendation system, such as the film's genre, the actors, the story, and even the director. The systems can propose movies based on a single attribute or a combination of two or more. The recommendation system in this paper is based on the tags created by combining genre, actors and description that the user may choose to watch. We have adopted a Content-based filtering technique in our project. A recommendation engine uses several algorithms to filter data and then recommends the most relevant items to consumers. If a user visits a movie site for the first time, the site will have no previous history of that user. In such cases, the user can search for their favourite movie genre or director to get a similar recommendation.

Movie Recommendation Systems, Content-Based Filtering, Movie recommendation, machine learning project.

"INTELLIGENT MOVIE RECOMMENDATION SYSTEM USING AI AND ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 2, page no.a152-a156, February-2022, Available :http://www.jetir.org/papers/JETIR2202019.pdf

"INTELLIGENT MOVIE RECOMMENDATION SYSTEM USING AI AND ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 2, page no. ppa152-a156, February-2022, Available at : http://www.jetir.org/papers/JETIR2202019.pdf