Movie Recommendation System and Data Analysis

We are living in a digital era, nowadays everything starting from shopping to entertainment is easily accessible online to all the age groups, thanks to the user-friendly interface. This technological advancement was maximized during COVID-19 and continues to flourish till now. But this development made about 29.1 percent of the population that consists of children under the age of 18 vulnerable to movies, shows having illegal and adult content. Not only this, even for adults it can be a tiresome process to scroll through a long list of movies on sites just to find that one movie of your taste. In such cases, a recommendation system will help the user filter out the content easily. In this paper, we have done detailed data analysis over the IMDB movie dataset and created a recommendation system where users can look for movies on the basis of actor, director, genre, language etc. This system works using the concept of correlation and feature engineering.