Earlier I had done sentiment analysis on news headlines for stock prediction but not on movies so it came to my mind to do it on movie and built a recommendation engine for it also.
What it does
This is a website which gives details about the movie you search with its cast , sentiment analysis of that movie i.e. overall rating with the recommendation of the others movie similar to the searched movie.
How we built it
This has been built using python , machine learning , flask and web scraping.The datasets has been taken from kaggle and web scraping done through Beautiful Soup.To know more about the cast of movie api key has been taken from tmdb.org . First the datasets were preprocessed and sentiment analysed was done on it and a recommendation engine was built and it has been made into website using python flask and deployed using heroku app.
Challenges we ran into
The challenges were to mange the data , transform them , deployed it on heroku because as the load on server gets high .
Accomplishments that we're proud of
The model was built successfully of what has been thought of.
What we learned
To make a recommendation system , do webscraping and manage them all.
What's next for Movie Recommendation System
To improve it's UI/UX , its loading time and currently it has hollywood movies only and in english so to add more other movies like in hindi , french and much more .
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