Recommendation systems play an important role in our everyday life. Starting from movie/music streaming sites like Netflix or Spotify to the most basic search engines, the core component is comprised of recommendation systems. Even the technology giant Google is known for its search engine above everything else. To emphasize its importance we aim to build a simple recommendation system using the IMDB movie database. Our finished web application can suggest similar movies based on the input provided by the user, considering factors like the plot of the movie, actors present in it, as well as the director. Needless to say, some factors would be common between the input movie and the recommended ones. The web app uses the scikit-learn python library, to match with the input movie with corresponding movies in the dataset with the highest similarity score. Its frontend is designed using Flask and it is deployed on Heroku. We aim to demystify the magic behind a recommendation system and provide an introduction to natural language processing also on the way.

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