Movie Recommendation system
Movie recommendation system that offers generalized recommendations to every user based on movie genre,cast and popularity.The model gives personalized recommendations based on the user's choice of genre and cast. Finally, the system suggests similar movies have a higher probability of being liked based on the movie selected by user.
- Sign-in functionality
- Restrictions and validations on the sign-in page
- Recommended movies similar to the user's selected movie
- Completely responsive frontend
Seamless landing page with Sign-in (Login) button.
- Frontend : HTML5, CSS3, JavaScript, BootStrap
- Backend : Python flask
- Database : MySQL
- ML model : Jupyter Notebook
Python : NumPy, Pandas, ast (Abstract Syntax Trees), pickle
ML : ntlk (Natural Language Toolkit), sklearn (scikit-learn)
SQLite : PyMySQL
Like/Dislike : The option to like or dislike a movie adds the movie to the user's like/dislike list. As of now, I am just accumulating the data. This can be further extended by using the like/dislike list to recommend movies to the user.
Watch Movie : The watch movie option currently displays the same movie intro for all the movies. In the future, it can be customized according to the movie selected.
Collabrative Filtering : The model currently uses a content-based recommendation system. It can be converted into a hybrid system by adding a collaborative filtering mechanism.