In this project, we use Content based recommender system. This is based on product description. Here we convert movie titles into a vector to find its cosine similarity. Similar movie would have a high cosine similarity and thus would be recommended to the user. We'll take use of the following parameters :-

Movies
Overviews
Taglines

In simple words. We'll analyze the text used in descriptions of movies to find similarity between movies and on the basis of it, predict output.