A python and pyqt base video player, which has a recommender system base on This Dataset. This system allows user to find 3 type of familiar movies related on it's movies in playlist.
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These are 3 types :
| Name |
|---|
| Content Recommender base on Cast and genre |
| Content Recommender base on overview on IMDb website |
| k-best movies filtered by weighted-rating |
That's simple. Pyqt control UI and video player. It has four option.
- Playlist which you can manage by selecting a movie and delete that from playlist
- Open File (Obviously there is no need to explain)
- AI. According to previous explanation return three type of movies
- Setting which allows you to change the number movies from each recommendation types.
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First, for further details check .
Upon completion of all routine processes like data cleaning, feature engineering (Eg. weighted_rating, ExtractGenres) and handling Nan values, 3 model ( or recommender system) provided.
- The first system is a simple scoring mechanism for calculating the top movies.
- The second system is based on overview of movies that utilizes TF-IDF.
- The third system is based on genre, crew and cast.
| Libraries | Links |
|---|---|
| TensorFlow | https://www.tensorflow.org |
| Numpy | https://numpy.org |
| Pandas | https://pandas.pydata.org |
| Matplotlib | https://matplotlib.org |
| Scikit-Learn | https://scikit-learn.org |
| Pyqt5 | https://riverbankcomputing.com/software/pyqt/ |
Make sure you have all of libraries in your env.; then run main.py.